Compute the Regression Analysis in SPSS using the data provided on self esteem and reading ability.

Chi Square and Regression

 

TYPE all of your answers in addition to the pictures of your work.

 

A store owner is trying to decide whether he should order equal amounts of four types of milk (skim, 1%, 2%, and whole). To help determine if certain kinds of milk are more popular, he records how many gallons of each kind of milk he sells over the course of a week. His data shows that he sold: 31 gallons of skim milk, 23 gallons of 1% milk, 37 gallons of 2% milk, and 25 gallons of whole milk. The owner is interested in whether the store sells equal amounts of the four types of milk.

Compute a Goodness of Fit Chi Square. Report and interpret your results including the value of chi square, degrees of freedom and statistical and practical significance.

df = k – 1

Where  = chi square, fo = frequency observed, fe = frequency expected, ϕ = phi (measure of practical significance)

Show your work here (for full credit you must show your work for all steps – type in below or attach a picture). Also show your work for the computation of phi.  10 points :

fo fe
Skim milk
1% milk
2% milk
Whole milk
Sum

Write out your interpretation including frequencies for all groups and use the following format for the reporting of the results, χ² () =  , p .05, Φ =) to report your results. 10 points

Santos et al. (1994) described the pique technique. They claimed that people are more likely to comply with strange requests than with “typical” ones, even if the strange request is larger.

To test this hypothesis, a researcher asked 160 strangers for money. He asked some people if they could spare a quarter, and asked others if they could spare 37 cents. He then recorded how many people gave him the amount requested and how many people did not.

Were people more likely to give the researcher 37 cents than they were to give him 25 cents?

Compute a Chi Square Test of Independence. Report and interpret your results including the value of chi square, degrees of freedom and statistical and practical significance.

Observed Frequencies

Show your work here (type in row totals, column totals and grand total here):

(for full credit you must show your work for all steps – type in below or attach a picture)

YES – Did give the $ NO – Did not give the $ Row Total
Asked for 25 cents 18 42
Asked for 37 cents 54 46
Column Total Grand Total =

 

Show your work here (for full credit you must show your work for all steps – type in below or attach a picture). Also show your work for the computation of phi.  10 points :

Expected Frequencies (For each cell compute the following: row total x column total/grand total)

YES – Did give the $ NO – Did not give the $
Asked for 25 cents
Asked for 37 cents

 

df = (ka – 1)(kb – 1)

(for full credit you must show your work for all steps – type in below or attach a picture)

 

YES – Did give the $ NO – Did not give the $
Asked for 25 cents
Asked for 37 cents

 

Write out your interpretation including frequencies for all groups and use the following format for the reporting of the results, χ² () =  , p .05, Φ =) to report your results. 10 points

 

A researcher wants to assess whether students’ level of prejudice predict attitudes toward racial profiling.  As part of a larger survey, students complete two scales pertaining to those variables.  Higher scores on the prejudice measure indicate greater prejudice and higher scores on the profiling scale indicate greater support for racial profiling.  Scores on both measures are obtained from each of 20 students.

Prejudice Profiling
X Y XY X2
7 5 35 49
4 4 16 16
5 3 15 25
6 7 42 36
2 2 4 4
3 4 12 9
6 7 42 36
4 5 20 16
8 6 48 64
9 8 72 81
6 6 36 36
5 3 15 25
4 4 16 16
6 5 30 36
2 4 8 4
6 8 48 36
5 4 20 25
7 8 56 49
8 4 32 64
7 9 63 49
Sum 110 106 630 676
Mean 5.5 5.3

 

Insert one picture for work for both c and d here and Type your answers below

Identify the predictor. 2 points

Identify the criterion. 2 points

Compute the regression line. 20 points

Using the regression line – identify the predicted profiling score for a person with a score of 8 for prejudice. 4 points

Peterson is interested in assessing whether self-esteem predicts reading ability. The data is as follows:

Self Esteem Reading Ability
4 13
6 10
7 16
8 13
10 17
11 12
13 14
13 17

 

Identify the predictor variable (IV) 1 point

Identify the criterion variable (DV) 1 point

Compute the Regression Analysis in SPSS using the data provided on self esteem and reading ability. Paste your output here (you will need to use a snipping tool to copy from SPSS, it will not allow you to copy and paste). Output has several parts – it must include: variables entered/removed, model summary, ANOVA, ad coefficients tables. 5 points

Report results in sentence format  see handout instructions on what to include and how to format it. 5 points