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2017-05-02 20:12:01

Workshop in Probability and Statistics from Start to Finish

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This workshop will teach you the fundamentals of statistics in order to give you a leg up at work or in school.

231 students enrolled

Current price: $10
Original price: $200
Discount:
95% off

30-Day Money-Back Guarantee

- 5 hours on-demand video
- 7 Supplemental Resources
- Full lifetime access
- Access on mobile and TV

- Certificate of Completion

What Will I Learn?

- By the end of this workshop you should be able to pass any introductory statistics course
- This workshop will teach you probability, sampling, regression, and decision analysis
- Able to learn lot of Statistics concepts

Requirements

- Basic knowledge of statistics

Description

Welcome to the course on "Workshop in Probability and Statistics from Start to Finish" This workshop is designed to help you make sense of basic probability and statistics with easy-to-understand explanations of all the subject's most important concepts. Whether you are starting from scratch or if you are in a statistics class and struggling with your assigned textbook or lecture material, this workshop was built with you in mind. In this workshop you will learn about Probability , Hypothesis Testing , Confidence Interval , Simple and Linear Regression Models , Sampling or survey sampling with complete Exercises , and PDF materials also provided for additional help .

Who is the target audience?

- People in business who want a better grasp of probability and statistics.
- Current students who are (or will soon be) taking a course in introductory statistics with their home institutions

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Curriculum For This Course

76 Lectures

04:49:58
+
–

Introduction to course
1 Lecture
09:49

+
–

Basic Probability and Statistics
11 Lectures
37:54

What is Set , Subset , Infinite and Finite Set , Universal and Null Set Etc Etc

05:27

Venn Diagram , Union of two sets , Intersection of two sets , Disjoint Set

02:56

Overlaping sets , Complement of a Set , Difference of two sets

02:06

What is Experiment , Trial ,Outcome , Random Experiment Sample Space?

03:39

Event , Simple Event , Composite or Compound Event and Equally Likely Events

03:23

Mutually Exclusive Events , Collectively Events , Independent & Dependent Events

04:01

Define Probability with Examples?

04:18

Find the Probability when Even or Odd numbers are rolled

03:48

Rules of Probability , Rules of Multiplication and Addition

03:16

Conditional Probability

03:03

Rules of Multiplication with Examples

01:57

+
–

Hypothesis testing
10 Lectures
36:31

What is Hypothesis , Statistical Hypothesis and Testing of Hypothesis?

01:58

Null Hypothesis and Alternative Hypothesis

01:58

Degree of Freedom , General Procedure for Testing of Hypothesis

01:05

Example 1

05:15

Example II - Is this a one or two tailed test.....??

03:09

Example of Testing Hypothesis about Population Proportion (Sample Size is Large)

03:15

Examples of Population Mean: Small Sample, Population Standard Deviation.....?

07:47

Test Statistic for the Difference between Two Means

04:26

Two Sample Tests about Proportions

07:14

Exercise

00:24

+
–

Confidence Interval
11 Lectures
41:12

What is Estimate , Estimator and Estimation?

03:47

Confidence interval and prediction interval

04:13

Normal population with sigma known

06:23

A random sample of size ,,,,,,,,, is taken from a normal population with a known variance. If the mean of the sample is ....... find 95% confidence limits for the population mean. ?

Another Example of Normal Population with sigma known

03:21

What is Student T-Distribution?

02:16

Confidence interval for difference of means

03:22

Examples of confidence interval for difference of means

05:18

Any population variance known/unknown large samples

05:17

Confidence Interval for population proportion

03:55

**Confidence Interval for Difference between Two Population Proportions, π _{1}−π_{2}**

Confidence Interval for Difference between Two Population Proportions, π1−π2

02:56

Exercise

00:24

+
–

Simple Linear Regression Analysis
11 Lectures
47:03

*The least squares principle is a criterion for fitting a specified model to observed data such that the sum of squares of the residuals (difference between observed and estimate value) is minimized? in detail.*

*The estimated model can be written?*

Regression Analysis

03:01

**Determine the regression equation.****Determine the value of....... when X is....?**

Examples of Regression Analysis

06:03

Examples with Interpretation

03:38

Standard Error of Estimate

06:44

Coefficient of determination

05:16

**Estimate the regression line of sales on price and interpret the results?****What is the part of the variation in sales which is not explained by the regression line?****Calculate coefficient of determination and standard error of estimate.?**

Interpretation of coefficient of determination

05:22

**Correlation Analysis**

**Pearson’s Product Moment Correlation Coefficient:**

Pearson’s product moment correlation coefficient, usually denoted by r, is one example of a correlation coefficient. It is a measure of the linear association ....................?

Correlation Analysis

04:27

**The Relationship among the Coefficient of Correlation, the Coefficient of Determination and the S.E of Estimate:**

Sum of square of regression =S.S.R =Regression=Explained variation........?

.............?

Relationship between Coefficient of Correlation , Determination and S.E

04:21

Test the significance of coefficient of correlation

05:27

**Inferences about the Slope Coefficient:**

The inferences about the regression coefficient can be made by t−test for the slope and F−test for the slope.

**Testing Hypotheses about Regression Coefficient**

Testing of hypothesis about regression coefficient

02:20

Exercise

00:24

+
–

Multiple Regression Model
11 Lectures
39:05

What is Multiple Regression?

03:18

Estimation of Multiple Linear Regression Model with Two Explanatory Variables ..

02:29

Introducing the formulas of Multiple Regression in deviation form

03:25

Solving the model of Multiple Regression model with example

10:06

What is Multiple Standard Error of Estimate?

03:14

How to find the values of Multiple standard error of estimate?

04:26

What is Coefficient of Multiple Determination?

02:18

How to find the values of coefficient of Multiple determination?

03:58

What is Adjusted Coefficient of Multiple Determinations?

03:16

How to find Adjusted Coefficient of Multiple Determination?

02:11

Exercise

00:24

+
–

Sampling and Sample Survey
11 Lectures
42:13

What is population? Sample and Sampling

01:36

Advantages of Sampling

02:09

Sampling design and sampling Survey

03:46

Sampling Distribution of the Sample Mean

05:54

What is Standard Error? Explanation with Examples

03:25

Sampling Distribution with Replacement

06:15

Sampling Distribution of the Difference between Means

01:58

Example of Sampling Distribution of the Difference between Means Part II

09:29

Example of Sampling Distribution of the Difference between Means Part II

03:24

Exercise

00:24

+
–

Analysis of Variance
10 Lectures
36:11

The F Distribution and Characteristics of the F Distribution

02:08

Example one

03:07

ANOVA Test and Assumptions

05:12

Preview
07:57

Inferences about Pairs of Treatment Means

02:10

Example of Inferences about Pairs of Treatment Means & difference of means

02:10

Two−Way Analysis of Variance

01:15

Example of Two−Way Analysis of Variance (part I)

07:28

Example of Two−Way Analysis of Variance (part II)

04:20

Exercise

00:24

About the Instructor

Instructor at Udemy

I have Specialization in Statistics , Finance and also teach Economics , Statistics and Mathematics to students in an academy and now I have started to teach online . I also hold

- Studied in Statistics and Finance from Punjab University
- I also hold Diplomas in Office Productivity and many Softwares
- Post Graduate Diploma in Business Administration and Finance.
- Bachelors in Science from Post Graduate College .
- Also hold diplomas in fashion , make up , beauty and cosmatics

Now I want to teach online and I'm very passionate about it.

I teach Economics, Mathematics, Statistics, Finance and English. Now i'm creating courses online in all these subjects.

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