Hypothesis testing in college level statistics - Part 1-

Learn how to test statistical hypotheses through well conceived lessons and fully solved numerous exercises with ease.
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Instructed by Luc Zio Academics / Math & Science
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  • Lectures 17
  • Length 1.5 hours
  • Skill Level Intermediate Level
  • Languages English
  • Includes Lifetime access
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About This Course

Published 3/2016 English

Course Description

The course covers the theory and application of testing statistical hypotheses. The material of the course is college level introductory statistics course for students majoring in various fields.
Testing statistical hypotheses is a result of teaching introductory statistics courses for over ten years at the college level. The course is written in an easy to understand way and draw upon several fully solved and explained problems to make it hands-on and practical. Each concept is immediately followed with illustrated examples and solved exercise so that you will learn by doing.

Content and Overview
This course of 17 lectures and 1.5 hours of content is suitable for a college student or anyone interested in understanding statistical tests of hypotheses in a hands-on way, at their own comfortable pace. It's very rich with examples and solved problems and do not pretend that you will understand things by just reading definitions and concepts.
My approach is hands-on: Concepts, examples and solved problems addressing all the concepts covered in the lectures. In addition, we have quizzes and the forum for questions.
After teaching statistics for over ten years to college students from various math background and interests, my lectures are designed to address all the questions that introductory statistics students tend to ask and the difficulties related to statistical tests of hypotheses.

What are the requirements?

  • Suggest taking my Normal and confidence interval courses as a pre-requisite
  • Know the Normal distribution and able to read the Standard normal table
  • Have ANY scientific calculator in order to calculate.

What am I going to get from this course?

  • Understand how to write statistical hypotheses and test them
  • Understand and test hypotheses about populations means for one sample
  • Understand and test hypotheses about populations proportions for one sample
  • Understand and test hypotheses about populations variances for one sample
  • Understand the relationship between confidence intervals and testing hypotheses

What is the target audience?

  • Anyone interested in analytics, data sciences
  • College and AP Statistics students
  • Business professionals interested in applied statistics
  • Introductory statistics course for college students

What you get with this course?

Not for you? No problem.
30 day money back guarantee.

Forever yours.
Lifetime access.

Learn on the go.
Desktop, iOS and Android.

Get rewarded.
Certificate of completion.

Curriculum

Section 1: Introduction to testing statistical hypotheses concepts
01:51

After this lecture you should be able to download the necessary statistical tables and other important files for the course.

02:25

In this lesson, we learn through examples what are statistical hypotheses.

03:53

This lecture covers the concepts of the Null and the alternative hypotheses with many examples that help the student understand the concepts.

05:11

This lecture provides examples to help the student identify the null and the alternative hypothesis in problems and also to write down the hypotheses.

08:56

This lecture provides detailed definitions of test of hypothesis, rejection or critical region, test statistics, type I and type II errors.

If you did not reject the null hypothesis when testing an hypothesis, then:
1 question
What statistical signification test do?
1 question
02:32

This lecture provide examples to help the student identify Type 1 and Type 2 errors

1 question

After conducting a statistical test, you conclude that the mean score of males differs significantly from the mean score of females. You have:

02:57

This lecture provides information about the steps for testing hypotheses

Section 2: Testing hypotheses about the population mean for one sample
09:22

This lecture explains how to test left and right tailed hypotheses about the population mean when the sample selected is large
(n >= 30). Detailed examples are provided to further explain the concept in a practical way.

Test of hypothesis Quiz about Rejection region
1 question
Test of hypothesis Quiz: conclusion
1 question
08:15

This lecture explains how to test a two-tailed hypothesis about the population mean when the sample selected is large (n>=30). Detailed solved exercises are provided to further illustrate the concepts.

Testing an hypothesis about a pop mean: quality control problem
1 question
1 question


Testing an hypothesis about a pop mean: quality control problem (3)
1 question
Testing an hypothesis about a pop mean: quality control problem (4)
1 question
Setting up an hypothesis about a population mean
1 question
09:50

This lectures explains how to test statistical hypotheses about the population mean when the sample selected is small (n <30) and the population we are sampling from is assumed to be normally distributed.

1 question

This quiz asks the student to setup the hypothesis to test.

Computing the test statistic about a student t distribution
1 question
Section 3: Testing statistical hypotheses about the population proportion for one sample
Testing statistical hypotheses about the population proportion for one sample
09:47
When testing an hypothesis about the population proportion
1 question
Compute the Z statistic for a test of a population proportion p
1 question
Section 4: Testing statistical hypotheses about the population variance for one sample
02:49

This lecture explains the chi square test and its properties. It also explains the point estimates of the population variance and standard deviation. The lecture provides a visual display of a family of chi square distributions with different degrees of freedom.

03:44

This lecture provides detailed tests of hypotheses about the population variance and standard deviation for the left and right tailed test. Solved exercises are provided to help students master the concepts.

05:27

This lecture provides detailed tests of hypotheses about the population variance and standard deviation for the two-tailed test. Solved exercises are provided to help students master the concepts.

Section 5: Testing hypotheses using P-values methods
09:21

This lecture explains how to compute the P-values when testing hypotheses about the population mean and proportion and how to make decisions about rejecting the null hypothesis based on the calculated p-value.

Based on this P-value, what decision would you have made
1 question
Section 6: Relationship between confidence intervals and hypotheses test
03:37

This lecture explains the relationship between confidence intervals and hypotheses testing. Students will be able to use confidences intervals and answer questions as to whether the null hypothesis should be rejected or not.

Section 7: Conclusion for the course
02:21

Testing hypotheses concluding remarks and next steps to take

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Instructor Biography

Luc Zio, Adjunct faculty of Math and Statistics

I  have over 18 years of work experience in the field of statistics as an Applied Statistician. For the last  twelve years, I have also  been teaching undergraduate college level statistics courses at St Petersburg College.  As an Applied Statistician, I have developed over the years a strong interest in using EXCEL as a statistical tool with my classes in order to give to the students real world hands-on experience with Statistics.

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