Transcript Social Science Reasoning Using Statistics

Thursday, October 3
Using Excel to conduct t-tests;
Review for Exam 2
Last Time
• We practiced figuring out which type of t-test to use when,
and we reviewed and practiced use of SPSS to conduct all
three type of t-tests.
• We also learned how to use sample statistics and the ttable to construct confidence intervals around point
estimates of population parameters.
• Today we will learn how to do t-tests using Excel, and we
will review for Monday’s exam
• Questions about material from last time before we move
on?
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 ttest.
Practice problem
You 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 problem
Now 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 (Tuesday 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