F STATISTIC REPORT ASSIGNMENT

F Statistic Report Assignment



F Statistic Report Assignment

Section I - Data File Description

In this assignment, we will calculate an F test, or ANOVA, and provide interpretations for it using the terminology we have learned in this course. Specifically, we will be returning to the IQ variable.

The two variables that we will be working on them are IQ and English.

The data set that we are going to work on it is IQ by the grade that participants had in their English.

•ENGG - Grade in English in ninth grade: 4 = A; 3 = B; and so on.

•IQ - IQ obtained from a group-administered IQ test.

Sample size:

The number of participants in this study is 88.

Section II - Assumptions, Data Screening, and Verification of Assumptions

An F-check is any statistical check in which the check statistic has an F-distribution under the null hypothesis. It is most often used when matching statistical forms that have been fit to a facts and figures set, in order to identify the form that best aligns the community from which the facts and figures were sampled.

*The hypothesis that the means of some normally circulated populations, all having the same standard deviation, are equal. This is perhaps the best-known F-test, and plays an important function in the investigation of variance (ANOVA).

*The hypothesis that a suggested regression form fits the data well. See Lack-of-fit sum of squares.

*The hypothesis that a facts and figures set in a regression analysis pursues the simpler of two suggested linear forms that are nested within each other.

*Scheffé's method for multiple comparisons change in linear models.

F-test of the equality of two variances

Main item: F-test of equality of variances

This F-test is exceedingly perceptive to non-normality.[2][3] Alternatives are Levene's check, Bartlett's check, and the Brown-Forsythe test. However, when any of these checks are undertook to test the underlying assumption of homoscedasticity (i.e. homogeneity of variance), as a initial step to testing for signify consequences in ANOVA, there is an increase in the experiment-wise kind I mistake rate.

Section III - Inferential Procedure, Hypotheses, Alpha Level (one paragraph)

H0: there is a significance difference in the variances of different groups.

H1: there is no significance difference in the variances different groups.

Level of significance: 0.05

Section IV - Interpretation

English

Case Processing Summary

engl

Cases

Valid

Missing

Total

N

Percent

N

Percent

N

Percent

iq

1

14

100.0%

0

.0%

14

100.0%

2

64

100.0%

0

.0%

64

100.0%

3

10

100.0%

0

.0%

10

100.0%

From the above table it can be found out that there are 14 people who have A grade in nine class, 64 ...