در این آموزش تصویری نحوه کار با توابع آماری در اکسل ، آشنایی با انواع داده ها و متغیرها ، انجام انواع محاسبات، محاسبه میانگین و میانه ، سازماندهی داده ها ، توزیع نمودار و … را می آموزید.

این دوره قسمت اول آمار در اکسل و محصول موسسه Lynda می باشد.

سرفصل های این دوره:

  • خطاهای نوع I و II
  • فرضیه تست میانگین
  • استفاده از قضیه حد مرکزی
  • استفاده از Z-test و آزمون t-test
  • تست فرضیه واریانس
  • توزیع مربع کای
  • درک نمونه مستقل
  • توزیع برای نمونه های مستقل
  • z و آزمون برای نمونه مستقل
  • آزمون t برای گروه های مستقل
  • نمونه همسان
  • توزیع ها برای نمونه همسان
  • آزمون t برای نمونه همسان
  • آزمون F تست فرضیه
  • آزمون F کلی
  • تحلیل واریانس
  • استفاده از ANOVA
  • تجزیه و تحلیل واریانس
  • اندازه گیری های مکرر چیست؟
  • انجام اقدامات مکرر
  • تعاملات آماری
  • دو عامل ANOVA
  • انجام دو عامل ANOVA
  • و …

عنوان دوره: Lynda Statistics with Excel Part One

مدت دوره: 3 ساعت و 18 دقیقه

نویسنده: Joseph Schmuller


Lynda Statistics with Excel Part One

Joseph Schmuller
3h 18m Appropriate for all

Understanding statistics is more important than ever. Statistical operations are the basis for decision making in fields from business to academia. However, many statistics courses are taught in cookbook fashion, with an emphasis on a bewildering array of tests, techniques, and software applications. In this course, part one of a series, Joseph Schmuller teaches the fundamental concepts of descriptive and inferential statistics and shows you how to apply them using Microsoft Excel.

He explains how to organize and present data and how to draw conclusions from data using Excel's functions, calculations, and charts, as well as the free and powerful Excel Analysis ToolPak. The objective is for the learner to fully understand and apply statistical concepts'not to just blindly use a specific statistical test for a particular type of data set. Joseph uses Excel as a teaching tool to illustrate the concepts and increase understanding, but all you need is a basic understanding of algebra to follow along.
Topics include:
Understanding data types and variables
Calculating probability
Understanding mean, median, and mode
Calculating variability
Organizing and graphing distributions
Sampling distributions
Making estimations
Testing hypothesis: mean testing, z- and t-testing, and more
Analyzing variance
Performing repeated measure testing
Understanding correlation and regression

5m 8s
10. Hypothesis Testing
5m 9s
The logic of hypothesis testing
2m 30s
Type I errors and type II errors
2m 39s
11. Mean Hypothesis Testing
7m 43s
Applying the central limit theorem
3m 28s
The z-test and the t-test
4m 15s
12. Variance Hypothesis Testing
3m 26s
Chi-square distribution
3m 26s
13. z and t Hypothesis Testing
14m 40s
Understanding independent samples
2m 40s
Distributions for independent samples
3m 33s
The z-test for independent samples
2m 57s
The t-test for independent samples
5m 30s
14. Matched Sample Hypothesis Testing
8m 57s
Matched samples
2m 20s
Distributions for matched samples
2m 45s
The t-test for matched samples
3m 52s
15. F-Test Hypothesis Testing
3m 32s
F-test overview
3m 32s
16. Analysis of Variance
10m 43s
More than two parameters
5m 38s
3m 9s
Applying ANOVA
1m 56s
17. After the Analysis of Variance
4m 23s
Types of post-ANOVA testing
1m 46s
Post-ANOVA planned comparisons
2m 37s
18. Repeated Measures Testing
7m 54s
What is repeated measures?
5m 18s
Perform repeated measures ANOVA
2m 36s
19. Hypothesis Testing with Two Factors
11m 35s
Statistical interactions
4m 31s
Two-factor ANOVA
4m 46s
Perform two-factor ANOVA
2m 18s
20. Regression
15m 30s
Regression line overview
5m 26s
Variation around the regression line
2m 57s
Analysis of variance for regression
3m 57s
Multiple regression analysis
3m 10s
21. Correlation
7m 0s
Correlation coefficient
2m 21s
Correlation and regression
2m 43s
Hypothesis testing with correlation
1m 56s
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