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Today we will learn how to do t-tests using excel, and we will review for Monday’s exam

Using Excel to compute t-tests

=ttest(array1,array2,tails,type)Select the arrays that you want to

compare, specify number of tails (1 or 2) and type of t-test (1=dependent, 2=independent w/equal variance assumed, 3=independent w/unequal variance assumed).

Returns the p-value associated with the t-test.

Practice problemYou are conducting an experiment about methods for

teaching reading. You randomly assign five students to an experimental reading intervention, and another five to receive instruction as usual in their classrooms. After the intervention, you measure the number of words each child can read correctly in one minute, and obtain the following results.

Group 1 (experimental): 30, 35, 40, 20, 32 Group 2 (usual instruction): 25, 30, 20, 18, 18 Use Excel to conduct a t-test to find out whether the

groups are different in reading ability at the end of the study.

Practice problemNow assume the scores represent pretest and

posttest scores for one group, before and after they received the reading intervention.

Posttest scores: 30, 35, 40, 20, 32 Pretest scores: 25, 30, 20, 18, 18 Use Excel to conduct a t-test to find out

whether the the children’s reading ability improved between the pretest and posttest.

Exam II (Monday 10/8) Covers first 11 chapters (emphasis on

chapters 9-11) Closed book (materials will be

provided) Bring calculator Bring pencil Emphasis on material covered in class Difficulty level similar to Exam I, but

much more material to know Some SPSS and Excel may be required

Old Material Terms from chapter 1 Ways to describe distributions (using tables, graphs,

numeric summaries of center and spread) Z-scores Probability Characteristics of the normal distribution Use of the unit normal table Central Limit Theorem & distribution of sample means Standard error of the mean (σM) Hypothesis testing (four steps) Effect sizes and power Type I and Type II error

New Material: t-tests•Similarities/differences among four inferential tests:

•One-sample Z test•One-sample t-test•Independent samples t-test•Paired samples t-test

•When to use which test•Formulae for each statistic

•Numerator (difference between means)•Denominator (standard error)•Degrees of freedom

•Use of the t-table with various alpha levels and one-tailed and two-tailed scenarios•Effect sizes•Estimation and confidence intervals

New Material: t-tests

•Assumptions of the t-tests•Levene’s test for equality of variance•Using SPSS/Excel to conduct t-tests

•Setting up the data properly•Knowing which commands to use•Interpreting the output