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آموزش آمار با Excel

دسته بندی ها: آموزش اکسل (Excel) ، آموزش آفیس (Microsoft office) ، آموزش های یودمی (Udemy)

آموزش-آمار-با-excel

این آموزش تصویری نحوه پیاده سازی و انجام محاسبات آماری با استفاده از Excel را فرامیگیرید.

این دوره آموزشی محصول موسسه Udemy می باشد.

سرفصل های دوره:

  • آمار توصیفی در مقابل آمار استنباطی بخش 1
  • آمار توصیفی در مقابل آمار استنباطی بخش 2
  • کار با متغیرها
  • کار با نوع متغیر
  • انواع اندازه گیری ها
  • مقدمه Excel
  • توزیع فراوانی در Excel بخش 1
  • توزیع فراوانی در Excel بخش 2
  • توزیع فراوانی در Excel بخش 3
  • توزیع فراوانی و امکانات آن
  • Dotplots و نمودار در Excel
  • نمودار هیستوگرام
  • فرکانس در مقابل فرکانس نسبی
  • کار با مجموعه Stemplots خلاصه توزیع
  • کار با میانگین، میانه، حالت بخش 1
  • کار با میانگین، میانه، حالت بخش 2
  • کار با میانگین، میانه، حالت بخش 3
  • کار با میانگین، میانه، حالت بخش 4
  • Boxplots در اکسل
  • اصلاح Boxplot
  • مفهوم عدم تقارن
  • محاسبه تقارن و در یک نمودار اماری بخش 1
  • محاسبه تقارن و در یک نمودار اماری بخش 2
  • محاسبه تقارن و در یک نمودار اماری بخش 3
  • توزیع نرمال قسمت 1
  • توزیع نرمال قسمت 2
  • توزیع نرمال چیست
  • استاندارد عادی توزیع نرمال
  • کار با انواع مشکلات
  • توزیع نرمال: PDF مقابل CDF، قسمت 1
  • توزیع نرمال: PDF مقابل CDF، قسمت 2
  • توزیع نرمال: PDF مقابل CDF، قسمت 3
  • کار با Scatterplots
  • مجموع خطاها مربعات (SSE)
  • ضریب همبستگی (R)
  • محاسبه R
  • SST و SSE چیست؟
  • کار با انواع داده ها
  • و...

عنوان دوره: Udemy Statistics with Excel

توضیحات:

to learn statistics using Excel to build more marketable skills or ace your college course? We'll help you through it with our super comprehensive 36 hour course broken down into easy to understand 159 lessons.
Each lesson begins with concept overviews before our instructor dives into step-by-step data manipulation in Excel. Data sets are downloadable so you can follow along.
Although our course is catered towards college students, professional students and even high school students taking the AP will find our information lifesaving.
Did we mention you'll also have an awesome teacher?
Dr. Son has a Ph.D. in Psychology and Cognitive Science, is a published researcher on how people learn and apply abstract concepts, and has been teaching college level statistics for over 10 years.
Category: Academics / Math & Science
    What are the requirements?
Knowledge of math up to Algebra 2
Microsoft Excel installed
    What am I going to get from this course?
Over 146 lectures and 35.5 hours of content!
Ace your college level General Statistics course
Master statistical analysis on Microsoft Excel
    What is the target audience?
College students in an introductory statistics course
Professionals looking to add statistical analysis to their Excel skillset
High school students taking the AP Statistics course

SECTION 1: Introduction 1 Descriptive Statistics vs. Inferential Statistics, Part 1 19:10 Roadmap Statistics Let's Think About High School Science Statistics = Math of Distributions Statistics Two Skills of Statistics Descriptive Statistics vs. Inferential Statistics: Apply to Distributions Populations vs. Samples Putting Together Descriptive/Inferential Stats & Populations/Samples Example 1: Descriptive Statistics vs. Inferential Statistics Example 2: Descriptive Statistics vs. Inferential Statistics Example 3: Sample, Parameter, Population, and Statistic Example 4: Sample, Parameter, Population, and Statistic 2 Descriptive Statistics vs. Inferential Statistics, Part 2 06:21 Example 1: Descriptive Statistics vs. Inferential Statistics Example 2: Descriptive Statistics vs. Inferential Statistics Example 3: Sample, Parameter, Population, and Statistic Example 4: Sample, Parameter, Population, and Statistic SECTION 2: About Samples: Cases, Variables, Measurements 3 About Samples: Cases, Variables, Measurements, Part 1 14:14 Data How Do We Get Data? Types of Variables 4 About Samples: Cases, Variables, Measurements, Part 2 17:56 Types of Measurements Types of Measurements (Scales) Example 1: Cases, Variables, Measurements Example 2: Which Scale of Measurement is Used? Example 3: What Kind of a Scale of Measurement is This? Example 4: Discrete vs. Continuous Variables. SECTION 3: Visualizing Distributions 5 Introduction to Excel, Part 1 07:14 Before Visualizing Distribution Excel: Organization Excel + Data 6 Frequency Distributions in Excel, Part 1 18:22 Preview Raw Data to Frequency Tables Example 1: Number of Births Example 2: Age Distribution Example 3: Height Distribution Example 4: Height Distribution of Males 7 Frequency Distributions in Excel, Part 2 13:47 Raw Data to Frequency Tables Example 1: Number of Births Example 2: Age Distribution Example 3: Height Distribution Example 4: Height Distribution of Males 8 Frequency Distributions in Excel, Part 3 06:36 Raw Data to Frequency Tables Example 1: Number of Births Example 2: Age Distribution Example 3: Height Distribution Example 4: Height Distribution of Males 9 Frequency Distributions and Features, Part 1 13:53 Roadmap Example #1 Example #2 Example #3 Example #4a Example #4b 10 Frequency Distributions and Features, Part 2 11:26 Summary Sketch Problem 1: Driver's License Sketch Problem 2: Life Expectancy Sketch Problem 3: Telephone Numbers Sketch Problem 4: Length of Time Used to Complete a Final Exam 11 Dotplots and Histograms in Excel, Part 1 15:24 Roadmap Previously Dotplots Dotplots: Pros and Cons Histograms 12 Dotplots and Histograms in Excel, Part 2 16:11 Histograms 13 Dotplots and Histograms in Excel, Part 3 10:59 Histograms: Pros and Cons Frequency vs. Relative Frequency Example 1: Dotplots vs. Histograms Example 2: Age of Pennies Dotplot Example 3: Histogram of Mammal Speeds Example 4: Histogram of Life Expectancy 14 Stemplots 12:17 What Sets Stemplots Apart? Example 1: What Do Stemplots Look Like? Example 2: Back-to-Back Stemplots Example 3: Quiz Grade Stemplot Example 4: Quiz Grade & Afterschool Tutoring Stemplot 15 Bar Graphs, Part 1 14:01 Review of Frequency Distributions Example 1: Bar Graph Do Shapes, Center, and Spread of Distributions Apply to Bar Graphs? 16 Bar Graphs, Part 2 08:41 Example 2: Create a Frequency Visualization for Gender Example 3: Cases, Variables, and Frequency Visualization Example 4: What Kind of Graphs are Shown Below? SECTION 4: Summarizing Distributions 17 Central Tendency: Mean, Median, Mode, Part 1 15:04 Central Tendency 1 Central Tendency 2 Summation Symbol Population vs. Sample Excel Examples Median vs. Mean Example 1: Mean Example 2: Using Summation Symbol Example 3: Average Calorie Count Example 4: Creating an Example Set 18 Central Tendency: Mean, Median, Mode, Part 2 10:23 Central Tendency 1 Central Tendency 2 Summation Symbol Population vs. Sample Excel Examples Median vs. Mean Example 1: Mean Example 2: Using Summation Symbol Example 3: Average Calorie Count Example 4: Creating an Example Set 19 Central Tendency: Mean, Median, Mode, Part 3 13:15 Central Tendency 1 Central Tendency 2 Summation Symbol Population vs. Sample Excel Examples Median vs. Mean Example 1: Mean Example 2: Using Summation Symbol Example 3: Average Calorie Count Example 4: Creating an Example Set 20 Central Tendency: Mean, Median, Mode, Part 4 09:35 Central Tendency 1 Central Tendency 2 Summation Symbol Population vs. Sample Excel Examples Median vs. Mean Example 1: Mean Example 2: Using Summation Symbol Example 3: Average Calorie Count Example 4: Creating an Example Set 21 Variability, Part 1 12:25 Variability (or Spread) Things to Think About Range, Quartiles and Interquartile Range Interquartile Range Example Variance and Standard Deviation Sum of Squares (SS) Population vs. Sample SD Population vs. Sample Example 1: Find the Mean and Standard Deviation of the Variable Friends in the Excel File Example 2: Find the Mean and Standard Deviation of the Tagged Photos in the Excel File Example 3: Sum of Squares Example 4: Standard Deviation 22 Variability, Part 2 14:53 Variability (or Spread) Things to Think About Range, Quartiles and Interquartile Range Interquartile Range Example Variance and Standard Deviation Sum of Squares (SS) Population vs. Sample SD Population vs. Sample Example 1: Find the Mean and Standard Deviation of the Variable Friends in the Excel File Example 2: Find the Mean and Standard Deviation of the Tagged Photos in the Excel File Example 3: Sum of Squares Example 4: Standard Deviation 23 Variability, Part 3 15:15 Variability (or Spread) Things to Think About Range, Quartiles and Interquartile Range Interquartile Range Example Variance and Standard Deviation Sum of Squares (SS) Population vs. Sample SD Population vs. Sample Example 1: Find the Mean and Standard Deviation of the Variable Friends in the Excel File Example 2: Find the Mean and Standard Deviation of the Tagged Photos in the Excel File Example 3: Sum of Squares Example 4: Standard Deviation 24 Five Number Summary & Boxplots, Part 1 17:02 Summarizing Distributions Boxplot: Visualizing 5 Number Summary Boxplots on Excel When are Boxplots Useful? How to Determine Outlier Status Modified Boxplot Example 1: Percentage Values & Lower and Upper Whisker Example 2: Boxplot Example 3: Estimating IQR From Boxplot Example 4: Boxplot and Missing Whisker 25 Five Number Summary & Boxplots, Part 2 17:58 Summarizing Distributions Boxplot: Visualizing 5 Number Summary Boxplots on Excel When are Boxplots Useful? How to Determine Outlier Status Modified Boxplot Example 1: Percentage Values & Lower and Upper Whisker Example 2: Boxplot Example 3: Estimating IQR From Boxplot Example 4: Boxplot and Missing Whisker 26 Five Number Summary & Boxplots, Part 3 14:08 Summarizing Distributions Boxplot: Visualizing 5 Number Summary Boxplots on Excel When are Boxplots Useful? How to Determine Outlier Status Modified Boxplot Example 1: Percentage Values & Lower and Upper Whisker Example 2: Boxplot Example 3: Estimating IQR From Boxplot Example 4: Boxplot and Missing Whisker 27 Five Number Summary & Boxplots, Part 4 07:59 Summarizing Distributions Boxplot: Visualizing 5 Number Summary Boxplots on Excel When are Boxplots Useful? How to Determine Outlier Status Modified Boxplot Example 1: Percentage Values & Lower and Upper Whisker Example 2: Boxplot Example 3: Estimating IQR From Boxplot Example 4: Boxplot and Missing Whisker 28 Shape: Calculating Skewness & Kurtosis, Part 1 08:55 Skewness Concept Calculating Skewness Interpreting Skewness Kurtosis Concept Calculating Kurtosis Interpreting Kurtosis Example 1: Shape of Distribution Example 2: Shape of Distribution Example 3:Shape of Distribution Example 4: Kurtosis 29 Shape: Calculating Skewness & Kurtosis, Part 2 11:31 Skewness Concept Calculating Skewness Interpreting Skewness Kurtosis Concept Calculating Kurtosis Interpreting Kurtosis Example 1: Shape of Distribution Example 2: Shape of Distribution Example 3:Shape of Distribution Example 4: Kurtosis 30 Shape: Calculating Skewness & Kurtosis, Part 3 11:37 Skewness Concept Calculating Skewness Interpreting Skewness Kurtosis Concept Calculating Kurtosis Interpreting Kurtosis Example 1: Shape of Distribution Example 2: Shape of Distribution Example 3:Shape of Distribution Example 4: Kurtosis 31 Normal Distribution, Part 1 19:45 What is a Normal Distribution Possible Range of Probabilities What is a Normal Distribution "Same" Shape: Illusion of Different Shape! Types of Problems Shape Analogy Example 1: The Standard Normal Distribution and Z-Scores Example 2: The Standard Normal Distribution and Z-Scores Example 3: Sketching and Normal Distribution Example 4: Sketching and Normal Distribution 32 Normal Distribution, Part 2 14:35 What is a Normal Distribution Possible Range of Probabilities What is a Normal Distribution "Same" Shape: Illusion of Different Shape! Types of Problems Shape Analogy Example 1: The Standard Normal Distribution and Z-Scores Example 2: The Standard Normal Distribution and Z-Scores Example 3: Sketching and Normal Distribution Example 4: Sketching and Normal Distribution 33 Standard Normal Distributions & Z-Scores, Part 1 16:41 Preview A Family of Distributions Normal Distribution vs. Standard Normal Distribution Z-Score, Raw Score, Mean, & SD Weird Z-Scores Excel Types of Problems Shape Analogy Example 1: Deaths Due to Heart Disease vs. Deaths Due to Cancer Example 2: Heights of Male College Students Example 3: Mean and Standard Deviation Example 4: Finding Percentage of Values in a Standard Normal Distribution 34 Standard Normal Distributions & Z-Scores, Part 2 11:39 A Family of Distributions Normal Distribution vs. Standard Normal Distribution Z-Score, Raw Score, Mean, & SD Weird Z-Scores Excel Types of Problems Shape Analogy Example 1: Deaths Due to Heart Disease vs. Deaths Due to Cancer Example 2: Heights of Male College Students Example 3: Mean and Standard Deviation Example 4: Finding Percentage of Values in a Standard Normal Distribution 35 Standard Normal Distributions & Z-Scores, Part 3 13:17 A Family of Distributions Normal Distribution vs. Standard Normal Distribution Z-Score, Raw Score, Mean, & SD Weird Z-Scores Excel Types of Problems Shape Analogy Example 1: Deaths Due to Heart Disease vs. Deaths Due to Cancer Example 2: Heights of Male College Students Example 3: Mean and Standard Deviation Example 4: Finding Percentage of Values in a Standard Normal Distribution 36 Normal Distribution: PDF vs. CDF, Part 1 18:33 Frequency vs. Cumulative Frequency Frequency vs. Cumulative Frequency Calculus in Brief PDF Integral of PDF = CDF Example 1: Cumulative Frequency Graph Example 2: Mean, Standard Deviation, and Probability Example 3: Mean and Standard Deviation Example 4: Age of Cars 37 Normal Distribution: PDF vs. CDF, Part 2 17:15 Frequency vs. Cumulative Frequency Frequency vs. Cumulative Frequency Calculus in Brief PDF Integral of PDF = CDF Example 1: Cumulative Frequency Graph Example 2: Mean, Standard Deviation, and Probability Example 3: Mean and Standard Deviation Example 4: Age of Cars 38 Normal Distribution: PDF vs. CDF, Part 3 19:51 Frequency vs. Cumulative Frequency Frequency vs. Cumulative Frequency Calculus in Brief PDF Integral of PDF = CDF Example 1: Cumulative Frequency Graph Example 2: Mean, Standard Deviation, and Probability Example 3: Mean and Standard Deviation Example 4: Age of Cars SECTION 5: Linear Regression 39 Scatterplots, Part 1 18:28 Previous Visualizations Compare & Contrast Summary Values Example Scatterplot Positive and Negative Association Linearity, Strength, and Consistency Summarizing a Scatterplot Example 1: Gapminder.org, Income x Life Expectancy Example 2: Gapminder.org, Income x Infant Mortality Example 3: Trend and Strength of Variables Example 4: Trend, Strength and Shape for Scatterplots 40 Scatterplots, Part 2 17:41 Previous Visualizations Compare & Contrast Summary Values Example Scatterplot Positive and Negative Association Linearity, Strength, and Consistency Summarizing a Scatterplot Example 1: Gapminder.org, Income x Life Expectancy Example 2: Gapminder.org, Income x Infant Mortality Example 3: Trend and Strength of Variables Example 4: Trend, Strength and Shape for Scatterplots 41 Scatterplots, Part 3 11:04 Previous Visualizations Compare & Contrast Summary Values Example Scatterplot Positive and Negative Association Linearity, Strength, and Consistency Summarizing a Scatterplot Example 1: Gapminder.org, Income x Life Expectancy Example 2: Gapminder.org, Income x Infant Mortality Example 3: Trend and Strength of Variables Example 4: Trend, Strength and Shape for Scatterplots 42 Regression, Part 1 14:48 Linear Equations Rough Line Regression - A "Center" Line Goal of Regression Prediction Error in Prediction Example 1: Residual Example 2: Large and Negative Residual Example 3: Positive Residual Example 4: Interpret Regression Line & Extrapolate 43 Regression, Part 2 17:05 Linear Equations Rough Line Regression - A "Center" Line Goal of Regression Prediction Error in Prediction Example 1: Residual Example 2: Large and Negative Residual Example 3: Positive Residual Example 4: Interpret Regression Line & Extrapolate 44 Least Squares Regression, Part 1 17:16 Best Fit Sum of Squared Errors (SSE) Why Squared? Quantitative Properties of Regression Line So How do we Find Such a Line? How Do We Find Slope (b1) Hoe Do We Find Intercept Example 1: Which of These Equations Fit the Above Data Best? Example 2: Find the Regression Line for These Data Points and Interpret It Example 3: Summarize the Scatterplot and Find the Regression Line. Example 4: Examine the Mean of Residuals 45 Least Squares Regression, Part 2 17:13 Best Fit Sum of Squared Errors (SSE) Why Squared? Quantitative Properties of Regression Line So How do we Find Such a Line? How Do We Find Slope (b1) Hoe Do We Find Intercept Example 1: Which of These Equations Fit the Above Data Best? Example 2: Find the Regression Line for These Data Points and Interpret It Example 3: Summarize the Scatterplot and Find the Regression Line. Example 4: Examine the Mean of Residuals 46 Least Squares Regression, Part 3 09:20 Best Fit Sum of Squared Errors (SSE) Why Squared? Quantitative Properties of Regression Line So How do we Find Such a Line? How Do We Find Slope (b1) Hoe Do We Find Intercept Example 1: Which of These Equations Fit the Above Data Best? Example 2: Find the Regression Line for These Data Points and Interpret It Example 3: Summarize the Scatterplot and Find the Regression Line. Example 4: Examine the Mean of Residuals 47 Least Squares Regression, Part 4 12:36 Best Fit Sum of Squared Errors (SSE) Why Squared? Quantitative Properties of Regression Line So How do we Find Such a Line? How Do We Find Slope (b1) Hoe Do We Find Intercept Example 1: Which of These Equations Fit the Above Data Best? Example 2: Find the Regression Line for These Data Points and Interpret It Example 3: Summarize the Scatterplot and Find the Regression Line. Example 4: Examine the Mean of Residuals 48 Correlation, Part 1 15:06 Summarizing a Scatterplot Quantitatively Correlation Coefficient ( r ) Trees vs. Forest Calculating r Relationship between Correlation and Slope Example 1: Find the Correlation between Grams of Fat and Cost Example 2: Relationship between r and b1 Example 3: Find the Regression Line Example 4: Find the Correlation Coefficient for this Set of Data 49 Correlation, Part 2 15:18 Summarizing a Scatterplot Quantitatively Correlation Coefficient ( r ) Trees vs. Forest Calculating r Relationship between Correlation and Slope Example 1: Find the Correlation between Grams of Fat and Cost Example 2: Relationship between r and b1 Example 3: Find the Regression Line Example 4: Find the Correlation Coefficient for this Set of Data 50 Correlation, Part 3 13:24 Summarizing a Scatterplot Quantitatively Correlation Coefficient ( r ) Trees vs. Forest Calculating r Relationship between Correlation and Slope Example 1: Find the Correlation between Grams of Fat and Cost Example 2: Relationship between r and b1 Example 3: Find the Regression Line Example 4: Find the Correlation Coefficient for this Set of Data 51 Correlation: r vs. r-squared, Part 1 18:33 R-squared Parsing Sum of Squared (Parsing Variability) What is SST and SSE? r-squared If the Correlation is Strong… If the Correlation is Weak… Example 1: Find r-squared for this Set of Data Example 2: What Does it Mean that the Simple Linear Regression is a "Model" of Variance? Example 3: Why Does r-squared Only Range from 0 to 1 Example 4: Find the r-squared for This Set of Data 52 Correlation: r vs. r-squared, Part 2 18:51 R-squared Parsing Sum of Squared (Parsing Variability) What is SST and SSE? r-squared If the Correlation is Strong… If the Correlation is Weak… Example 1: Find r-squared for this Set of Data Example 2: What Does it Mean that the Simple Linear Regression is a "Model" of Variance? Example 3: Why Does r-squared Only Range from 0 to 1 Example 4: Find the r-squared for This Set of Data 53 Correlation: r vs. r-squared, Part 3 15:20 R-squared Parsing Sum of Squared (Parsing Variability) What is SST and SSE? r-squared If the Correlation is Strong… If the Correlation is Weak… Example 1: Find r-squared for this Set of Data Example 2: What Does it Mean that the Simple Linear Regression is a "Model" of Variance? Example 3: Why Does r-squared Only Range from 0 to 1 Example 4: Find the r-squared for This Set of Data 54 Transformations of Data, Part 1 10:35 Why Transform? Shape-preserving vs. Shape-changing Transformations Common Shape-Preserving Transformations Common Shape-Changing Transformations Change Just One Variable? Both? Example 1: Create, Graph, and Transform the Data Set Example 2: Create, Graph, and Transform the Data Set Example 3: What Kind of Model would You Choose for this Data? Example 4: Transformation of Data 55 Transformations of Data, Part 2 16:24 Why Transform? Shape-preserving vs. Shape-changing Transformations Common Shape-Preserving Transformations Common Shape-Changing Transformations Change Just One Variable? Both? Example 1: Create, Graph, and Transform the Data Set Example 2: Create, Graph, and Transform the Data Set Example 3: What Kind of Model would You Choose for this Data? Example 4: Transformation of Data SECTION 6: Collecting Data in an Experiment 56 Sampling & Bias, Part 1 13:06 Descriptive vs. Inferential Statistics To tackle Generalization… Defining Samples and Populations Why Use Sampling? Goal of Sampling: Avoiding Bias Sampling Bias: Bias from Bas Sampling Methods Response Bias: Bias from "Bad" Data Collection Methods Example 1: What Kind of Biases? Example 2: What Biases Might Arise? Example 3: What Kind of Biases? Example 4: What Kind of Biases? 57 Sampling & Bias, Part 2 14:52 Descriptive vs. Inferential Statistics To tackle Generalization… Defining Samples and Populations Why Use Sampling? Goal of Sampling: Avoiding Bias Sampling Bias: Bias from Bas Sampling Methods Response Bias: Bias from "Bad" Data Collection Methods Example 1: What Kind of Biases? Example 2: What Biases Might Arise? Example 3: What Kind of Biases? Example 4: What Kind of Biases? 58 Sampling & Bias, Part 3 12:30 Descriptive vs. Inferential Statistics To tackle Generalization… Defining Samples and Populations Why Use Sampling? Goal of Sampling: Avoiding Bias Sampling Bias: Bias from Bas Sampling Methods Response Bias: Bias from "Bad" Data Collection Methods Example 1: What Kind of Biases? Example 2: What Biases Might Arise? Example 3: What Kind of Biases? Example 4: What Kind of Biases? 59 Sampling & Bias, Part 4 14:05 Descriptive vs. Inferential Statistics To tackle Generalization… Defining Samples and Populations Why Use Sampling? Goal of Sampling: Avoiding Bias Sampling Bias: Bias from Bas Sampling Methods Response Bias: Bias from "Bad" Data Collection Methods Example 1: What Kind of Biases? Example 2: What Biases Might Arise? Example 3: What Kind of Biases? Example 4: What Kind of Biases? 60 Sampling Methods 14:16 Biased vs. Unbiased Sampling Methods Probability Sampling Methods Example 1: Which Type(s) of Sampling was this? Example 2: Describe How to Take a Two-Stage Sample from this Book Example 3: Sampling Methods Example 4: Cluster Sample Plan 61 Research Design, Part 1 17:53 Descriptive vs. Inferential Statistics Variables and Relationships Not Every Type of Study is an Experiment… Category III Why CAN'T the Other Strategies Determine Causation? What Makes Experiments Special? Methods of Control Experiment Terminology Blind How Categories Relate to Statistics Example 1: Research Design Example 2: Research Design Example 3: Research Design Example 4: Research Design 62 Research Design, Part 2 16:14 Descriptive vs. Inferential Statistics Variables and Relationships Not Every Type of Study is an Experiment… Category III Why CAN'T the Other Strategies Determine Causation? What Makes Experiments Special? Methods of Control Experiment Terminology Blind How Categories Relate to Statistics Example 1: Research Design Example 2: Research Design Example 3: Research Design Example 4: Research Design 63 Research Design, Part 3 19:28 Descriptive vs. Inferential Statistics Variables and Relationships Not Every Type of Study is an Experiment… Category III Why CAN'T the Other Strategies Determine Causation? What Makes Experiments Special? Methods of Control Experiment Terminology Blind How Categories Relate to Statistics Example 1: Research Design Example 2: Research Design Example 3: Research Design Example 4: Research Design 64 Between and Within Treatment Variability, Part 1 15:45 Experimental Designs Two Types of Variability Updated Goal of Experimental Design Example: Drugs and Driving Different Types of Random Assignment Randomized Block Design Between-subject Variable vs. Within-subject Variable Example 1: Design a Completely Random, Matched Pair, and Repeated Measures Experiment Example 2: Block Design Example 3: Completely Randomized Designs Example 4: Completely Random, Matched Pairs, or Repeated Measures Experiments? 65 Between and Within Treatment Variability, Part 2 10:28 Experimental Designs Two Types of Variability Updated Goal of Experimental Design Example: Drugs and Driving Different Types of Random Assignment Randomized Block Design Between-subject Variable vs. Within-subject Variable Example 1: Design a Completely Random, Matched Pair, and Repeated Measures Experiment Example 2: Block Design Example 3: Completely Randomized Designs Example 4: Completely Random, Matched Pairs, or Repeated Measures Experiments? 66 Between and Within Treatment Variability, Part 3 15:12 Experimental Designs Two Types of Variability Updated Goal of Experimental Design Example: Drugs and Driving Different Types of Random Assignment Randomized Block Design Between-subject Variable vs. Within-subject Variable Example 1: Design a Completely Random, Matched Pair, and Repeated Measures Experiment Example 2: Block Design Example 3: Completely Randomized Designs Example 4: Completely Random, Matched Pairs, or Repeated Measures Experiments? SECTION 7: Review of Probability Axioms 67 Sample Spaces, Part 1 15:06 Why is Probability Involved in Statistics Taste Test with Coffee Drinkers Creating a Probability Model D'Alembert vs. Necker Problem with D'Alembert's Model Covering Entire Sample Space Where Do Probabilities Come From? Checking whether Model Matches Real World Example 1: Law of Large Numbers Example 2: Possible Outcomes Example 3: Brands of Coffee and Taste Example 4: How Many Different Treatments are there? 68 Sample Spaces, Part 2 12:38 Why is Probability Involved in Statistics Taste Test with Coffee Drinkers Creating a Probability Model D'Alembert vs. Necker Problem with D'Alembert's Model Covering Entire Sample Space Where Do Probabilities Come From? Checking whether Model Matches Real World Example 1: Law of Large Numbers Example 2: Possible Outcomes Example 3: Brands of Coffee and Taste Example 4: How Many Different Treatments are there? 69 Sample Spaces, Part 3 10:04 Why is Probability Involved in Statistics Taste Test with Coffee Drinkers Creating a Probability Model D'Alembert vs. Necker Problem with D'Alembert's Model Covering Entire Sample Space Where Do Probabilities Come From? Checking whether Model Matches Real World Example 1: Law of Large Numbers Example 2: Possible Outcomes Example 3: Brands of Coffee and Taste Example 4: How Many Different Treatments are there? 70 Addition Rule for Disjoint Events, Part 1 10:48 Disjoint Events Meaning of "or" Addition Rule for Disjoin Events General Addition Rule Generalized Addition Rule Example 1: Which of These are Mutually Exclusive? Example 2: What is the Probability that You will Have a Combination of One Heads and Two Tails? Example 3: Engagement Party Example 4: Home Owner's Insurance 71 Addition Rule for Disjoint Events, Part 2 09:34 Disjoint Events Meaning of "or" Addition Rule for Disjoin Events General Addition Rule Generalized Addition Rule Example 1: Which of These are Mutually Exclusive? Example 2: What is the Probability that You will Have a Combination of One Heads and Two Tails? Example 3: Engagement Party Example 4: Home Owner's Insurance 72 Conditional Probability, Part 1 15:00 "or" vs. "and" vs. Conditional Probability "and" vs. Conditional Probability Tree Diagram Defining Conditional Probability Common Contexts for Conditional Probability Example 1: Drug and Disease Example 2: Marbles and Conditional Probability Example 3: Cards and Conditional Probability Example 4: Votes and Conditional Probability 73 Conditional Probability, Part 2 15:51 "or" vs. "and" vs. Conditional Probability "and" vs. Conditional Probability Tree Diagram Defining Conditional Probability Common Contexts for Conditional Probability Example 1: Drug and Disease Example 2: Marbles and Conditional Probability Example 3: Cards and Conditional Probability Example 4: Votes and Conditional Probability 74 Conditional Probability, Part 3 15:03 "or" vs. "and" vs. Conditional Probability "and" vs. Conditional Probability Tree Diagram Defining Conditional Probability Common Contexts for Conditional Probability Example 1: Drug and Disease Example 2: Marbles and Conditional Probability Example 3: Cards and Conditional Probability Example 4: Votes and Conditional Probability 75 Conditional Probability, Part 4 11:18 "or" vs. "and" vs. Conditional Probability "and" vs. Conditional Probability Tree Diagram Defining Conditional Probability Common Contexts for Conditional Probability Example 1: Drug and Disease Example 2: Marbles and Conditional Probability Example 3: Cards and Conditional Probability Example 4: Votes and Conditional Probability 76 Independent Events, Part 1 11:10 Preview Independent Events & Conditional Probability Non-independent and Independent Events Defining Independent Events Multiplication Rule Example 1: Which of These Pairs of Events are Independent? Example 2: Health Insurance and Probability Example 3: Independent Events Example 4: Independent Events 77 Independent Events, Part 2 13:07 Independent Events & Conditional Probability Non-independent and Independent Events Defining Independent Events Multiplication Rule Example 1: Which of These Pairs of Events are Independent? Example 2: Health Insurance and Probability Example 3: Independent Events Example 4: Independent Events SECTION 8: Probability Distributions 78 Introduction to Probability Distributions, Part 1 17:42 Sampling vs. Probability Missing Insight: Probability Distributions From Sample Spaces to Probability Distributions The Random Variable Expected Value Example 1: Probability Distributions Example 2: Probability Distributions Example 3: Probability Distributions Example 4: Probability Distributions 79 Introduction to Probability Distributions, Part 2 17:44 Sampling vs. Probability Missing Insight: Probability Distributions From Sample Spaces to Probability Distributions The Random Variable Expected Value Example 1: Probability Distributions Example 2: Probability Distributions Example 3: Probability Distributions Example 4: Probability Distributions 80 Introduction to Probability Distributions, Part 3 11:49 Sampling vs. Probability Missing Insight: Probability Distributions From Sample Spaces to Probability Distributions The Random Variable Expected Value Example 1: Probability Distributions Example 2: Probability Distributions Example 3: Probability Distributions Example 4: Probability Distributions 81 Introduction to Probability Distributions, Part 4 09:22 Sampling vs. Probability Missing Insight: Probability Distributions From Sample Spaces to Probability Distributions The Random Variable Expected Value Example 1: Probability Distributions Example 2: Probability Distributions Example 3: Probability Distributions Example 4: Probability Distributions 82 Expected Value & Variance of Probability Distributions, Part 1 19:19 Discrete vs. Continuous Random Variables Mean and Variance Review Example Situation Some Special Cases… Linear Transformations n Independent Values of X Compare These Two Situations Two Random Variables, X and Y Example 1: Expected Value & Variance of Probability Distributions Example 2: Expected Values & Standard Deviation Example 3: Expected Winnings and Standard Deviation 83 Expected Value & Variance of Probability Distributions, Part 2 16:13 Discrete vs. Continuous Random Variables Mean and Variance Review Example Situation Some Special Cases… Linear Transformations n Independent Values of X Compare These Two Situations Two Random Variables, X and Y Example 1: Expected Value & Variance of Probability Distributions Example 2: Expected Values & Standard Deviation Example 3: Expected Winnings and Standard Deviation 84 Expected Value & Variance of Probability Distributions, Part 3 18:05 Discrete vs. Continuous Random Variables Mean and Variance Review Example Situation Some Special Cases… Linear Transformations n Independent Values of X Compare These Two Situations Two Random Variables, X and Y Example 1: Expected Value & Variance of Probability Distributions Example 2: Expected Values & Standard Deviation Example 3: Expected Winnings and Standard Deviation 85 Binomial Distribution, Part 1 19:34 Discrete Probability Distributions Binomial Distribution Multiplicative Rule Review How Many Outcomes with k "Successes" P (X=k) Expected Value and Standard Deviation in a Binomial Distribution Example 1: Coin Toss Example 2: College Graduates Example 3: Types of Blood and Probability Example 4: Expected Number and Standard Deviation 86 Binomial Distribution, Part 2 18:25 Discrete Probability Distributions Binomial Distribution Multiplicative Rule Review How Many Outcomes with k "Successes" P (X=k) Expected Value and Standard Deviation in a Binomial Distribution Example 1: Coin Toss Example 2: College Graduates Example 3: Types of Blood and Probability Example 4: Expected Number and Standard Deviation 87 Binomial Distribution, Part 3 17:02 Discrete Probability Distributions Binomial Distribution Multiplicative Rule Review How Many Outcomes with k "Successes" P (X=k) Expected Value and Standard Deviation in a Binomial Distribution Example 1: Coin Toss Example 2: College Graduates Example 3: Types of Blood and Probability Example 4: Expected Number and Standard Deviation SECTION 9: Sampling Distributions of Statistics 88 Introduction to Sampling Distributions, Part 1 14:12 Probability Distributions vs. Sampling Distributions Same Logic Simulating Samples Connecting Sampling and Research Methods with Sampling Distributions Simulating a Sampling Distribution Logic of Sampling Distributions General Method of Simulating Sampling Distributions Questions that Remain Example 1: Mean and Standard Error of Sampling Distribution Example 2: What is the Best Way to Describe Sampling Distributions? Example 3: Matching Sampling Distributions Example 4: Mean and Standard Error of Sampling Distribution 89 Introduction to Sampling Distributions, Part 2 16:45 Probability Distributions vs. Sampling Distributions Same Logic Simulating Samples Connecting Sampling and Research Methods with Sampling Distributions Simulating a Sampling Distribution Logic of Sampling Distributions General Method of Simulating Sampling Distributions Questions that Remain Example 1: Mean and Standard Error of Sampling Distribution Example 2: What is the Best Way to Describe Sampling Distributions? Example 3: Matching Sampling Distributions Example 4: Mean and Standard Error of Sampling Distribution 90 Introduction to Sampling Distributions, Part 3 17:16 Probability Distributions vs. Sampling Distributions Same Logic Simulating Samples Connecting Sampling and Research Methods with Sampling Distributions Simulating a Sampling Distribution Logic of Sampling Distributions General Method of Simulating Sampling Distributions Questions that Remain Example 1: Mean and Standard Error of Sampling Distribution Example 2: What is the Best Way to Describe Sampling Distributions? Example 3: Matching Sampling Distributions Example 4: Mean and Standard Error of Sampling Distribution 91 Sampling Distribution of the Mean, Part 1 15:49 Special Case of General Method for Simulating a Sampling Distribution Using Simulations to See Principles behind Shape of SDoM Using Simulations to See Principles behind Center (Mean) of SDoM Using Simulations to See Principles behind Standard Deviation of SDoM Central Limit Theorem Comparing Population, Sample, and SDoM Answering the "Questions that Remain" Example 1: Mean Batting Average Example 2: Mean Sampling Distribution and Standard Error Example 3: Sampling Distribution of the Mean 92 Sampling Distribution of the Mean, Part 2 11:22 Special Case of General Method for Simulating a Sampling Distribution Using Simulations to See Principles behind Shape of SDoM Using Simulations to See Principles behind Center (Mean) of SDoM Using Simulations to See Principles behind Standard Deviation of SDoM Central Limit Theorem Comparing Population, Sample, and SDoM Answering the "Questions that Remain" Example 1: Mean Batting Average Example 2: Mean Sampling Distribution and Standard Error Example 3: Sampling Distribution of the Mean 93 Sampling Distribution of the Mean, Part 3 15:55 Special Case of General Method for Simulating a Sampling Distribution Using Simulations to See Principles behind Shape of SDoM Using Simulations to See Principles behind Center (Mean) of SDoM Using Simulations to See Principles behind Standard Deviation of SDoM Central Limit Theorem Comparing Population, Sample, and SDoM Answering the "Questions that Remain" Example 1: Mean Batting Average Example 2: Mean Sampling Distribution and Standard Error Example 3: Sampling Distribution of the Mean 94 Sampling Distribution of the Mean, Part 4 12:15 Special Case of General Method for Simulating a Sampling Distribution Using Simulations to See Principles behind Shape of SDoM Using Simulations to See Principles behind Center (Mean) of SDoM Using Simulations to See Principles behind Standard Deviation of SDoM Central Limit Theorem Comparing Population, Sample, and SDoM Answering the "Questions that Remain" Example 1: Mean Batting Average Example 2: Mean Sampling Distribution and Standard Error Example 3: Sampling Distribution of the Mean 95 Sampling Distribution of the Mean, Part 5 13:23 Special Case of General Method for Simulating a Sampling Distribution Using Simulations to See Principles behind Shape of SDoM Using Simulations to See Principles behind Center (Mean) of SDoM Using Simulations to See Principles behind Standard Deviation of SDoM Central Limit Theorem Comparing Population, Sample, and SDoM Answering the "Questions that Remain" Example 1: Mean Batting Average Example 2: Mean Sampling Distribution and Standard Error Example 3: Sampling Distribution of the Mean 96 Sampling Distribution of Sample Proportions, Part 1 19:12 Intro to Sampling Distribution of Sample Proportions (SDoSP) Notation What's the Difference? Binomial Distribution vs. Sampling Distribution of Sample Proportions Example 1: Sampling Distribution of Sample Proportions Example 2: Sampling Distribution of Sample Proportions Example 3: Sampling Distribution of Sample Proportions Example 4: Sampling Distribution of Sample Proportions 97 Sampling Distribution of Sample Proportions, Part 2 18:41 Intro to Sampling Distribution of Sample Proportions (SDoSP) Notation What's the Difference? Binomial Distribution vs. Sampling Distribution of Sample Proportions Example 1: Sampling Distribution of Sample Proportions Example 2: Sampling Distribution of Sample Proportions Example 3: Sampling Distribution of Sample Proportions Example 4: Sampling Distribution of Sample Proportions 98 Sampling Distribution of Sample Proportions, Part 3 16:37 Intro to Sampling Distribution of Sample Proportions (SDoSP) Notation What's the Difference? Binomial Distribution vs. Sampling Distribution of Sample Proportions Example 1: Sampling Distribution of Sample Proportions Example 2: Sampling Distribution of Sample Proportions Example 3: Sampling Distribution of Sample Proportions Example 4: Sampling Distribution of Sample Proportions SECTION 10: Inferential Statistics 99 Introduction to Confidence Intervals, Part 1 18:24 Inferential Statistics Two Problems with This Picture… Which Parameters are Known? Confidence Interval - Goal When We Don't Know Example 1: Confidence Intervals Example 2: Confidence Intervals Example 3: Confidence Intervals Example 4: Confidence Intervals 100 Introduction to Confidence Intervals, Part 2 11:19 Inferential Statistics Two Problems with This Picture… Which Parameters are Known? Confidence Interval - Goal When We Don't Know Example 1: Confidence Intervals Example 2: Confidence Intervals Example 3: Confidence Intervals Example 4: Confidence Intervals

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