Data Analysis Report

Data Analysis Report

Data Description

The data which is used for the analysis is the ADD dataset from Howell's textbook, which is available on course web page. In 1965, second-grade teachers in a number of schools in Vermont were asked to complete a questionnaire indicating the extent to which each student exhibited behaviors associated with attention deficit disorder (ADD).  Based on the questionnaire, an ADD “score” was computed for each student (with higher scores indicating more ADD-like behaviors).  The questionnaires for the same children were again completed when the children were in fourth and fifth grades.  The children were followed through high school, and in 1985 Howell and Huessy reported some data from this study.  The variables in the data set are as follows:

Variable in the Data

ID

ID number

ADDSC

Average of the three ADD scores

SEX

1=male; 2=female

REPEAT

1 = repeated at least one grade; 0 = did not repeat a grade

IQ

IQ obtained from a group-administered test

ENGL

Level of English in ninth grade: 1=college prep; 2=general; 3=remedial

ENGG

Grade in English in ninth grade: 4=A; 3=B; etc.

GPA

Grade point average in ninth grade

SOCPROB

Social problems in ninth grade: 1=yes; 0=no

DROPOUT

1 = dropped out before completing high school; 0 = did not drop out

Hypothesis

Null Hypothesis: There exist no effect of gender on the IQ scores.

Alternate Hypothesis: There exist an effect of gender on the IQ scores.

Level of Significance

For the purpose of the study we will use level of significance .05. The significance level of a test is a traditional frequentist statistical hypothesis testing concept. In simple cases, it is defined as the probability of making a decision to reject the null hypothesis when the null hypothesis is actually true (a decision known as a Type I error, or "false positive determination"). The decision is often made using the p-value: if the p-value is less than the significance level, then the null hypothesis is rejected. The smaller the p-value, the more significant the result is said to be.

Independent Sample T-Test

The Independent-Samples T Test procedure tests the significance of the difference between two sample means. Also displayed are:

Descriptive statistics for each test variable

A test of variance equality

A confidence interval for the difference between the two variables (95% or a value you specify)

Usually, the groups in a two-sample t test are fixed by design, and the grouping variable has one value for each group. However, there are times when assignment to one of two groups can be made on the ...