Скачать или смотреть Statistical Inference Procedures

In this lecture we review statistical inference procedures for a single population parameter for the situation in which the estimator of the parameter is Normally distributed. In particular, we review how to test hypotheses about the parameter, as well as how to construct confidence interval estimates of the parameter. We do this for two scenarios. First, we look at the scenario in which the variance of the estimator is known. We then look at the more common and realistic scenario in which the variance of the estimator is unknown. We will use these procedures early on in the course. As we progress, we will generalize and expand upon these results in ways that will allow us to test more complex hypotheses.

Here is an outline of the material covered in this video:

Inferences about a population parameter when the variance of its estimator is known
Hypothesis testing - Z tests
Confidence interval estimation - Z intervals
Inferences about a population parameter when the variance of its estimator is unknown
Hypothesis Testing - t tests
Confidence Interval Estimation - t intervals

Next lecture in this series:    • The Simple Linear Regression Model  
Previous lecture in this series:    • Characteristic Roots and Characteristic Ve...  
First lecture in this series:    • Introduction to Linear Regression  

Here is the textbook we are using:
Title: "Introduction to Linear Regression Analysis 5th Edition"
Authors: Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining.
ISBN-13: 978-0470542811
ISBN-10: 0470542810
Link on Amazon: https://www.amazon.com/Introduction-R...

Software Packages Used:
Get access to SAS for free: https://www.sas.com/en_us/software/on...
Minitab: https://www.minitab.com/en-us/

You can navigate to a particular topic in the lecture by clicking on a timecode below:

Timecodes

0:00 Introduction
1:49 The point estimator of the parameter and its sampling distribution
6:05 Standardized version of the parameter estimator and its sampling distribution
8:05 Normality assumption
9:28 Inference procedures for the parameter when the standard error of its point estimator is known
9:38 Hypothesis tests about the parameter when the standard error of its point estimator is known
16:36 Confidence interval estimation of the parameter when the standard error of its point estimator is known
21:22 Inference procedures for the parameter when the standard error of its point estimator is unknown
21:31 Studentized version of the parameter estimator and its sampling distribution
24:44 Hypothesis tests about the parameter when the standard error of its point estimator is unknown
30:15 Confidence interval estimation of the parameter when the standard error of its point estimator is unknown
34:52 Squared Studentized version of the parameter estimator and its sampling distribution
36:09 Hypothesis tests about the parameter using the squared Studentized version of the parameter estimator