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Running head: SPSS DATA 1

Analysis of Data Using SPSS

Student’s Name

Institutional Affiliation

SPSS DATA 2

Analysis of Data Using SPSS

Lesson 40 exercises 1-4 p.263

Kristen is interested in evaluating whether the method of cooking potato chips affects the taste of

the chips. She has 48 individuals volunteer to participate in her potato chip study. Each

participant tastes chips, cooked using three different methods: fried in animal fat (Chip=1), fried

in canola oil (chip=2), and baked (chip=3). Individuals are instructed to indicate which type of

potato chips they prefer: chip type 1, chip type 2, chip type 3. Kristen hypothesizes that

individuals will prefer potato chips that are friend in canola oil over those fried in animal fat or

baked.

1. Use the method reviewed in the presentation to weight the cases for this data set. (no

points—done in data file)

H0: The method of cooking potato chips affects the taste of the chips

H1: The method of cooking potato chips does not affect the taste of the chips

Research question: Does the method of cooking potato chips affects the taste of the

chips?

Case Processing Summary

Cases

Valid

Missing

Total

Percent

Method of cooking potato

chips * Number who

preferred each type of chip

100.0%

0.0%

100.0%

Method of cooking potato chips * Number who preferred each type of chip Cross tabulation

SPSS DATA 3

Count

Number who preferred each type of chip

Total

7.00

8.00

33.00

Method of cooking potato

chips

Fried in animal fat

Fried in Canola oil

Baked

Total

Chi-Square Tests

Value

Asymptotic

Significance (2-

sided)

Pearson Chi-Square

96.000

.000

Likelihood Ratio

80.352

.000

Linear-by-Linear Association

.047

.828

N of Valid Cases

a. 6 cells (66.7%) have expected count less than 5. The minimum

expected count is 1.02.

2. a. Observed frequency for potato chips fried in canola oil=33

b. P-value is 0.000

a. c. χ

value is 96.000

3. Expected frequencies for the three types of potato chips is 16. The number obtained by

diving total number of volunteers by number of categories (48 / 3 = 16).

4. A Chi-square test of independence was calculated comparing how methods of cooking

potato chips affect taste of chips. A significant difference in groups preference for chips

was found (χ

(4) =96, p<0.05.

Exercise 1-4 p. 269-270

The following helpful tips are numbered to correspond with the exercise number to which they

refer (a dash indicates that no tips are needed):

SPSS DATA 4

Paste SPSS output and answer a, b, d, and e underneath (skip c). For letter “e”, this question is

asking specifically about effect size. (2 for output; a, b, d, and e = 2 points each)

a) b. Computed only for a 2x2 table

H0: There is no relationship between the females who enrolled in advanced math courses

and them being raised by either their fathers or both parents

H1: There is a relationship between the females who enrolled in advanced math courses

and them being raised by either their fathers or both parents

Research question: Does a father or both parents influence the enrollment of female

students in advanced math courses.

Symmetric Measures

Value

Approximate

Significance

Nominal by

Nominal

Phi

-.275

.002

Cramer's

.275

.002

N of Valid Cases

130

SPSS DATA 5

Case Processing Summary

Cases

Valid

Missing

Total

Percent

Parents of female high

school student * Math

classes

130

100.0%

0.0%

130

100.0%

Parents of female high school student * Math classes Cross tabulation

Math classes

Total

advance

d math

Some

advanc

ed math

Parents of female high

school student

Primarily father

Count

Expected

Count

26.1

3.9

30.0

% within

Parents of

female high

school

student

70.0%

30.0%

100.0%

Father and mother

Count

100

Expected

Count

86.9

13.1

100.0

% within

Parents of

female high

school

student

92.0%

8.0%

100.0%

Total

Count

113

130

Expected

Count

113.0

17.0

130.0

% within

Parents of

female high

school

student

86.9%

13.1%

100.0%

SPSS DATA 6

Chi-Square Tests

Value

Asymptotic

Significance

(2-sided)

Exact Sig. (2-

sided)

Exact Sig.

(1-sided)

Pearson Chi-Square

9.826

.002

Continuity Correction

7.986

.005

Likelihood Ratio

8.434

.004

Fisher's Exact Test

.004

Linear-by-Linear

Association

9.751

.002

N of Valid Cases

130

a. 1 cells (25.0%) have expected count less than 5. The minimum expected count is 3.92.

SPSS DATA 7

3. a) The percentage of females who took some advanced math classes is 13.1%

b) The percentage of females who were primarily raised by their father and took no

advanced math classes is 70%.

c) ACTUALLY

d) X

= 9.826

e) 27 strength of relationship between taking advanced math classes and level of

parenting.

f) A 2x2 contingency table analysis was conducted to determine the relationship between

fathers only vs fathers and mothers and the enrollment of advanced math courses. A

significant interaction was found (χ

(1), N=130) = 9,83, p <.01. The effect size was .27,

which showed a high level of strength.

Exercises 1–5, p. 273

Billie wishes to test the hypothesis that overweight individuals tend to eat faster than normal-

weight individuals. To test this hypothesis, she has two assistants sit in a McDonald’s restaurant

and identify individuals who order the Big Mac special (Big Mac, large fries, and large Coke) for

lunch. The Big Mackers, as they are affectionately called by the assistants, are classified as

overweight, normal-weight, or neither overweight nor normal weight. The assistants identify 10

overweight and 30 normal-weight Big Mackers. The assistants record the amount of time it takes

for the individuals to complete their Big Mac special meals. The SPSS data file contains two

variables, a grouping variable with two levels, overweight (= 1) and normal weight (= 2), and

time in seconds to eat the meal.

H0: Overweight individuals do not eat faster than normal-weight individuals

SPSS DATA 8

H1: Overweight individuals tend to eat faster than normal-weight individuals

Research question: Does overweight individuals eat faster than normal-weight individuals?

1. Mann-Whitney U test

Ranks

weight

Mean Rank

Sum of Ranks

Time in Seconds

overweight

8.30

83.00

normal weight

24.57

737.00

Total

Test Statistics

Time in

Seconds

Mann-Whitney U

28.000

Wilcoxon W

83.000

-3.811

Asymp. Sig. (2-tailed)

.000

Exact Sig. [2*(1-tailed Sig.)]

.000

Exact Sig. (2-tailed)

.000

Exact Sig. (1-tailed)

.000

Point Probability

.000

a. Grouping Variable: weight

b. Not corrected for ties.

a. p value=0.00

b. z value corrected for ties=-3.811

c. Mean rank for normal-weight individuals=24.57

2. An independent-samples t test.

Group Statistics

weight

Mean

Std. Deviation

Std. Error Mean

Time in Seconds

overweight

589.00

42.615

13.476

normal weight

698.40

82.949

15.144

SPSS DATA 9

Independent Samples Test

Levene's Test for Equality of Variances

t-test for Equality of Means

Sig.

Sig. (2-tailed)

Time in Seconds

Equal variances assumed

2.745

.106

-3.975

.000

Equal variances not

assumed

-5.397

30.828

.000

2. According to the independent sample test chart shown above, p value=0.106; the p-

value for the independent sample test, p=0.1.6 is greater than the p-value of the

Mann-Whitney U test, p=0.00.

3. A Mann-Whitney test indicated that the rate of eating was higher for overweight

individuals than for normal weight individuals (Mdn=672), U=28.00, p=0.00. Since

p=0.00<p value=0.05, we reject the null hypothesis and conclude that overweight

individuals tend to eat faster than normal-weight individuals

4. The graph below shows the distribution of the eating rates of overweight individuals

and normal-weight individuals

SPSS DATA

Histogram

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