EDL 7150
Inferential Statistics

Course Calendar and Assignments 
Fall 2012.
(Click Here for the current assignment)

Prior to the first class Meeting

You should compete the following before we meet on August 22:

Install the Excel Data Analysis Tool Pack.

Peruse this website: Become familiar with the content of the various pages and sections.

Session 1 Aug. 22 Class activity: Review of basic statistical concepts

Overview of the course, review of the syllabus.

Introduction to the online statistics textbooks and other resources: 

VassarStats

HyperStat Online,

StatTrek

Research Methods Knowledge Base

Introductory PowerPoint presentation.

Trying out the Excel Data Analysis ToolPac

Before the next session, complete the following:

Respond to the Competency Pre-assessment. You will be given a similar assessment at the end of the second week of class.

Point your browser to the Vassar Stats online textbook and read Chapters 1 and 2.

Be sure you can articulate the differences between various scales of measurement: nominal, ordinal, interval, and ratio. Be prepared to differentiate between the notions of reliability and validity of measures and measuring instruments. Pay attention to the discussions of variables in the text.

Statistics deals with several types of distributions, some imperial (i.e., manifest) and some theoretical.  Be sure you know the difference. Distributions are the subject of Chapter 2.  Also, know how to describe a distribution in terms of measures of central tendency, variability, and skew. In this chapter you will encounter terms such as deviation scores, mean-squared deviation, sums of squares, samples, populations, statistics, parameters, and so forth. These are all important terms in statistics-- understanding these terms is critical to continuing in this course. When I talk about sums of squares, or SS, for instance, you should know that I am talking about.

You may be given a quiz next week over the material in these two chapters.

Session 2 Aug. 29
Class activities: 

Using Excel to compute various statistics.

Introduction to Probability, Probability Distributions and Calculators

Before the next session, complete the following:

Next week, you will be introduced to, and use, SPSS to compute a variety of descriptive statistics and graphs of distributions. In preparation, read Chapters 1-3 in HyperStat Online.

Read the Descriptive Statistics chapter in StatTrek

Download my short paper on Summation Operators and complete (to be turned in the next time we meet) the exercises at the end of the paper.

Before the following session (Session 4, Sep. 12) Complete the following:

Read my Paper on Probability and Probability Distributions. You can reserve the sections on the Chi-square and t distributions for later.

Read Chapter 4 (Intro to Probability) and Chapter 5 (Normal Distributions) in HyperStat Online.

In Chapter 4, in the Subsection on the Binominal distribution, take the Free Tutorial on Using Excel’s Binomial Function.

In Chapter 5, Subsection 4 (Converting to Percentiles) tryout the z-calculator.

Also, in Chapter 5, Subsection 5 (Area Under a Portion of the Normal Curve), check out, and try using, the z table.  

In addition, read Chapters 5 ab 6 in the Vassar Stats online textbook.

Also, check out the Answers to Pre-Assessment

 

Session 3 Sep. 5

SPSS Session: Descriptive statistics, charts, and graphs.

Before the next session, complete the following:

Complete the assignment given two weeks ago under "Before Sep 12..."

Session 4 Sep. 12

More on Probability and Probability Distributions

Answers to the exercises at the end of the paper on Summation Operators can be found HERE.

By the end of this week, complete the following:

Solve the probability problem given HERE

In RMKB, read the chapter on Measurement. This is a long chapter, but, since measurement is one of the basic tools of research and statistics, the chapter is critically important. This chapter complements Chapter 1 in the Vassar Stats online textbook.

The subsection on Construct Validity discusses several types of validity, threats to validity, and various approaches for establishing validity. All doctoral students should be familiar with these concepts.

The subsections on Reliability, and Levels of Measurement (which repeats some of the material covered earlier) also, are critically important.

The article, Procedures for estimating internal consistency reliability, prepared by the Iowa Technical Adequacy Project (ITAP) describes Coefficient Alpha and how to compute it. The article also shows how to use Excel to compute Coefficient Alpha. If you find yourselves, later, constructing an instrument, or even using an existing instrument, to measure some attribute, you will need to know how to compute internal consistency reliability.

I once used a Motivations for Reading instrument to measure elementary school students interest in reading. The instrument can be found HERE, and an Excel file containing the responses, HERE.

Use the guidelines given in the Procedures article to compute the alpha-reliability of my administration of the Motivations for Reading instrument.

Since many of you may want to use a survey in your dissertation research, you should read the subsection on Survey Research. Again, this is material all doctoral students are expected to know.

There are many types of surveys that can be used to measure human attributes. Three of these, discussed, are Likert scaling, Thurston scaling, and Guttman scaling. Be aware of the relative advantages and disadvantages of each, and know how they are constructed.

Session 5 Sep. 19

 

SPSS Session: Testing hypotheses using independent and dependent samples.

Last week I mentioned how some (naive)  researchers sometimes fail to recognize the proper unit of analysis, either in their own research or in the research of others. Here is a brief paper on Unit of Analysis that is well worth your reading.

This week we move into what is generally considered the heart of statistics: testing hypotheses about population parameters.

We do this using sample statistics. I say this because we are never interested in the obtained value of sample statistics themselves.
Instead we are interested in what the sample statistics tell us about the population parameters. 

First you will learn how to compute these tests using SPSS. Next week, which will be an asynchronous, online session, you will be guided
through process by instruction on this web page for next week.

Class activity:  

From what I have seen (posted on the ning and sent to me privately) you are having a lot of difficulty in solving the out of class probability problem. So, I thought I'd give you the Solution to the Out of Class Probability Problem now. We can talk about it tonight

Testing Hypotheses of Differences

Tests for comparing two independent samples

Student t Test for Independent Samples

Mann-Whitney U Test

Wilcoxon Independent Samples Test

Tests for comparing two dependent samples

Student t test for dependent samples

Use the Sign Test to perform a non-parametric solution to the t test scenario given in the previous example. Again, try programming the test in Excel.

McNemar's Test for Matched Pairs

Wilcoxon matched pairs signed ranks test

You can find Excel solutions to these problems HERE.

Before the next session, complete the following:

Read Chapters 9, 10, and 11 in the Vassar Stats online textbook.

Session 6 Sep. 26

ONLINE SESSION (Asynchronous)

Hypothesis Testing  

You began exploring tests for hypothesis last week (using SPSS). Here, you will be led through a few scenarios using procedures available on the web as well as Excel. 

For instance, suppose we are interested in the lunch-time caloric intake at lunchtime among middle school students. Obviously, we cannot measure this for ALL middle school students. Instead, we take a representative (usually random) sample of middle school students and measure their caloric intake at lunchtime, compute the average (a statistic) and use this as an estimate of the caloric intake of all students.

Suppose we have data that a healthy lunchtime caloric intake for average middle school students is 700 calories (I don't really know how accurate this is). If the average caloric intake of our sample of middle school students is 850 calories, can we conclude that the population from which our sample was drawn is eating, on average, too many calories at lunchtime? This is a problem in statistical inference and requires an hypothesis test.

During this session, I will  also provide some discussion of null hypothesis, sampling error, Type I and Type II errors, and some statistical procedures for testing null hypotheses.

By the end of this week, complete the following:  

Complete Out-of-Class Problem No. 2

In  HyperStat Online, read the chapters on Estimation (Chapters 7 & 8) and Hypothesis Testing (Chapter 9).

In the chapter on Estimation, make sure you have a firm grasp of the concept of a standard error and margin of error.

Know how to compute the variance the standard error of the mean and a confidence interval around a mean.

In the chapter on Hypothesis Testing: pay close attention to the section on Foundations of Testing. Know how to test whether a sample mean is equal to some predetermined value, and test the difference between independent means and dependent (paired) means.

You may find the discussion found at the following links particularly useful in understanding this chapter. 

HYPOTHESIS TESTING,

ONE AND TWO-TAILED t-TESTS,

ERRORS IN HYPOTHESIS TESTING
and

Testing Hypotheses About Single Means

Also, in the Chapter on Hypothesis Testing, understand and know how to compute the power of a statistical test.

Finally, in this chapter, be able to differentiate among situations where a chi-square test is appropriate for testing goodness of fit, homogeneity, and independence.

NOTE: Problem Set No. 1 is now available. Completion of these problems is due by the end of day on Sunday October 14. Use this Answer Sheet to record and submit your responses.

Session 7 Oct. 3 Using Excel, and VassarStats to compute tests involving means.

Class activity:

By the end of this week, complete the following:

Read Chapter 13 & 14 in the Vassar Stats online textbook.

Read Chapter 12 in HyperStat Online.

The next time we meet you will be introduce to the SPSS procedures, Oneway and Univariate General Linear Model. Familiarize yourself with these procedures in SPSS.

Complete Problem Set No. 1 (Answer Sheet) for recording your answers. Compete Problem Set 1 before October 15. 
Answers will be released  on October 15.)

Oct. 12 Holiday (Fall break)

Just added: Short paper on Effect Size. It would probably be a good idea to read this paper.

Session 8 Oct. 17  ANOVA with SPSS.

Class Activity

Today you will be shown how to compute, and interpret, a one-way analysis of variance using SPSS.

By the end of this week, complete the following:

Read Chapter 16 in the Vassar Stats online textbook and Chapter 13 in HyperStat Online.

Also, read my Introduction to Factorial Analysis of Variance and my brief paper on Partitioning Sums of Squares in ANOVA

 

Session 9 Oct. 24  Factorial Analysis of Variance

Class Activity

Today we will show how to compute a factorial analysis of variance using Excel, VassarStats, and SPSS

By the end of this week, complete the following:

Read all of Chapter 3, including the appendices, in the Vassar Stats online textbook

Read Chapter 15 in HyperStat Online.

Read my Introduction to Linear Regression and my paper on Partitioning Sums of Squares in Simple Linear Regression.

Session 10 Oct. 31 Correlation and Regression

Class activity:  

Using Excel, VassarStats and SPSS to compute:

Correlation

Pearson Product Moment Correlation (rxy).

Spearman Rho (ρxy) Correlation.

Regression Analysis

Prediction
Explanation

Before the next time we meet (Nov. 7), complete the following:

Read my brief General Overview of Regression Analysis

Under Index to Scenarios, do the following problems:

          º Correlations among GPA, SAT, Etc. for College Students

                    º Parts 1, 2, and 3.  

º Correlations among ses, SES, class rank, and SAT scores

          º Items 1 through 4.

Under Instructional Stuff for Statistics do the following problem.

º Introduction to Linear Regression Analysis (an Example)

Read Chapters 15 & 17 in the Vassar Stats online textbook.

 

Session 12 Nov. 7 

Online

Class activity:

Questions, Answers, Explanations

Before the next session, complete the following:

 

Session 13 Nov. 14
Repeated Measures ANOVA

Using SPSS and VassarStats to compute a Repeated Measures ANCOVA.

By the end of this week, complete the following:

 

Nov. 21 Holiday (Thanksgiving)
Session 14 Nov. 28 TBA
Session 15 Dec. 5 TBA
Session 16 Dec 12 TBA