در این آموزش تصویری با تجزیه و تحلیل آماری در Excel آشنا می شوید. این دوره تجزیه و تحلیل های آماری ، استفاده از ابزارها در اکسل ، کار با فرمول ها و توابع را آموزش می دهد. در ادامه نحوه ایجاد جدول ، ساخت histogram ، شناسایی خطا و اشکال زدایی برنامه را می آموزید.

این دوره آموزشی محصول موسسه Udemy است.

سرفصل های این دوره:

  • تجزیه و تحلیل های آماری
  • کار با مفاهیم آماری
  • تکنیک های کار با محاسبات آماری
  • استفاده از جدول
  • کار با فرمول ها در اکسل
  • نحوه استفاده از جداول
  • نحوه استفاده از نمودارها
  • استفاده از تابع فرکانس
  • نحوه ساخت histogram
  • نحوه استفاده از PivotTable
  • توصیف داده ها با استفاده روشهای عددی
  • نحوه استفاده از آمار های توصیفی
  • محاسبه کوواریانس
  • استفاده از توزیع های احتمالی
  • انتخاب نمونه داده ها
  • تعریف فرضیه ها
  • شناسایی خطا
  • اشکال زدایی برنامه
  • و…

عنوان دوره: Udemy Doing Basic Statistical Analysis Using MS Excel

مدت دوره: 4 ساعت

نویسنده: Dr. Ash Narayan Sah

توضیحات:

Udemy Doing Basic Statistical Analysis Using MS Excel

Dr. Ash Narayan Sah
4 hours


Descriptive statistics using MS Excel course offers clear cut knowledge of descriptive statistics tools using MS Excel.
Today, as a reseracher or a manager you must know how to convert data into information that may aid in the decision making process.
This course put interpretation and decision making with the help of data at the forefront.
The prime objective of this course is to demonstrate how to use MS Excel 2007 for statistical anlaysis using step by step method.
The following methods of analysis are included:
Graphing Techniques
Frequency Analysis
Numerical Techniques
Mean, Median, Mode Analysis
Range, Standard Deviation, Variance Analysis
Skewness and Kurtosis Analysis
Complete Descriptive Analysis with example
This course will be useful for all business professionals, marketing managers, financial analysts, economists, and students doing foundation courses in statistics, perhaps students in their second course or social or business researchers.
What are the requirements?
Knowledge of MS Excel is desirable.
What am I going to get from this course?
Over 32 lectures and 4 hours of content!
Learn meaning of descriptive statistics
Know summarizing data by graphical methods
Learn summarizing data by numerical methods
What is the target audience?
This descriptive statistics course is meant for those who enrolled in introductory statistics courses.
For thos who are familiar with statistics but don't know how to use MS excel for statistical analysis.


Section 1: Overview of Data and Statistics
Lecture 1
Introduction
03:08
Lecture 2
Meaning of Statistics
15:26
Lecture 3
Characteristics of Statistics
12:16
Lecture 4
Nature and Scope of Statistics
10:01
Lecture 5
Applications in Business and Economics
11:36
Lecture 6
Data and Nominal and Ordinal Scale
08:47
Lecture 7
Interval and Ratio Scale
06:37
Lecture 8
Types of Data
10:07
Lecture 9
Types of Statistics
03:39
Lecture 10
Limitations of Statistics
06:06
Lecture 11
Role of Computer in Statistical Analysis
01:30
Lecture 12
Review Excercise
Article
Section 2: Descriptive Analytics: Summarizing Data by Graphical Methods
Lecture 13
Introduction
02:14
Lecture 14
Introduction to Summarizing data by Graphical Methods
05:16
Lecture 15
Line Graph
05:49
Lecture 16
Simple Bar Graph and Multiple Bar Graph
11:28
Lecture 17
Simple Bargraph Excel Demonstration
04:54
Lecture 18
Multiple Bar graph Excel Demonstration
05:15
Lecture 19
Subdivided Bar Graph and Percentage Bar Graph
17:01
Lecture 20
Subdivided Bar Graph Excel Demonstration
04:06
Lecture 21
Percentage Bar Graph Excel Demonstration
04:46
Lecture 22
Pie Chart
08:15
Lecture 23
Pie Chart Excel Demonstration
08:24
Lecture 24
Scatter Diagram
06:26
Lecture 25
Frequency Distribution
10:07
Section 3: Descriptive Analytics: Summarizing Data by Numerical Methods
Lecture 26
Introduction to Summarizing data by numerical methods
01:06
Lecture 27
Measures of Central Tendency
09:44
Lecture 28
Measures of Dispersion
18:28
Lecture 29
Measures of Shape
08:55
Lecture 30
Numerical Summary Excel Demonstration
05:09
Lecture 31
Descriptive Statistics using data analysis
11:48
Lecture 32
Review Excercise