Section 8.1
Estimating Population Means
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HAWKES LEARNING SYSTEMS
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Objectives
o Determine the best point e
Lesson 8.3
Section 8.3 outlines the procedure for testing the population proportion. Z scores and the proportion
formulas are used in these tests. You can review the proportion symbols and formulas on
Lesson 8.1
Section 8.1 is an introduction to statistical testing. You will have two ideas or hypotheses when doing a statistical test.
One of these ideas is the null hypothesis. This hypothesis is tha
Lesson 7.1
In this chapter we begin looking at ESTIMATION of population parameters using sample statistics.
So how do we estimate the population mean using the sample mean as a point estimate?
In 7.1,
8.3 Testing a Proportion p
Statistics
Shirkey
1. Establish the null and alternate hypothesis Ho: p = k; H1: p <, >, or k
2. Determine a level of significance
3. Sketch and label the curve
4. Calculat
Statistics 9.1 Notes
Shirkey
Scatter Diagram: graph with (x,y) pairs plotted. x is called the explanatory variable, y the response variable.
See fig. 9-1 p. 531.
The main idea here is to try to find t
Lesson 8.2
Section 8.2 describes the procedure for testing the population mean.
When is known (p. 426) (from a preliminary study): observed test statistic is
We did this type of problem in the previou
Lesson 3.3
Section 3.3 explains the use of percentiles and the box-and-whisker plot.
Percentiles (p. 122) are used to show what percentage of the data values are at or below the value in question. You
Lesson 6.4
In previous sections of chapter 6, we used population means and population standard deviations without really saying
much about it. Population measures such as these are called parameters.
8.1 Introduction to Statistical Tests
Statistics - Shirkey
In the previous chapter, we used confidence intervals to estimate parameters. Now, we perform hypothesis
tests to help us make informed decis
Lesson 9.1
Section 9.1 covers scatter diagrams and linear correlation.
Scatter Diagram: graph with (x,y) pairs plotted. x is called the explanatory variable, y the response variable.
See fig. 9-1 p. 5