MGTO 324

Workshop 3: SPSS Data Management

Activity 1

Collect the following information from any 40 “subjects” Age

Estimate it if you cannot access the data

Gender Height

(1 “very short” to 7 “very high”)

Weight (1 “very light” to 7 “very heavy”)

Physical attractiveness (1 “not attractive” to 7 “very attractive”)

Shoes’ major color

SPSS data management

Rule of thumb One row for one “subject” One column for one “variable” At least give one column to identify the

“subject ID” How many variables do we have?

SPSS data management

Essential steps Defining and labeling variables

Give a good name for each variable

Defining the nature of the variables Continuous, ordinal, or categorical (Nominal)

Assigning and labeling values for categorical variables

Missing values

SPSS data management

Basic statistics Descriptive statistics

Mean, Frequency

Correlation Mean Comparison

SPSS data management

Basic statistics Descriptive statistics

Mean, Frequency

Statistics

RATING10

0

2.8000

3.0000

4.00

1.2293

Valid

Missing

N

Mean

Median

Mode

Std. Deviation

subject rating subject rating

1 4 6 4

2 3 7 2

3 4 8 1

4 1 9 2

5 4 10 3

SPSS data management

Basic statistics Descriptive statistics

Mean, Frequency

RATING

2 20.0 20.0 20.0

2 20.0 20.0 40.0

2 20.0 20.0 60.0

4 40.0 40.0 100.0

10 100.0 100.0

1.00 very slow

2.00 slow

3.00 fast

4.00 very fast

Total

ValidFrequency Percent

ValidPercent

Cumulative Percent

SPSS data management Basic statistics

Correlation The marketing manager of Oliver’s super sandwiches in Hong

Kong collected 100 comment cards which were voluntarily completed by customers. Questions on the comment cards include Menu Variety, Taste, Value for Money, Atmosphere, and Revisit. He wanted to see if these questions were associated with each other.

SPSS data management

Basic statistics Correlation

Correlations

1.000 -.083 .600** -.084 .282**

. .414 .000 .405 .004

100 100 100 100 100

-.083 1.000 -.135 -.254* -.181

.414 . .181 .011 .072

100 100 100 100 100

.600** -.135 1.000 .176 .417**

.000 .181 . .079 .000

100 100 100 100 100

-.084 -.254* .176 1.000 .524**

.405 .011 .079 . .000

100 100 100 100 100

.282** -.181 .417** .524** 1.000

.004 .072 .000 .000 .

100 100 100 100 100

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

Pearson Correlation

Sig. (2-tailed)

N

MENU

TASTE

VALUE

ATMOSPH

REVISIT

MENU TASTE VALUE ATMOSPH REVISIT

Correlation is significant at the 0.01 level (2-tailed).**.

Correlation is significant at the 0.05 level (2-tailed).*.

SPSS data management

Basic statistics Mean comparison

City 1 City 2

Victoria Winnipeg

n 25 25

mean $446.04 $518.92

s.d. $78.16 $57.43

SPSS data management

Basic statistics Mean comparison

Independent Samples Test

.838 .365 -3.757 48 .000 -72.88 19.398 -111.882 -33.878

-3.757 44.066 .001 -72.88 19.398 -111.972 -33.788

Equal variances assumed

Equal variances notassumed

HYDROF Sig.

Levene's Test forEquality of Variances

t df Sig. (2-tailed)Mean

DifferenceStd. ErrorDifference Lower Upper

95% ConfidenceInterval of the

Difference

t-test for Equality of Means

SPSS data management

In class exercise Based on your collected data, write a brief report

telling me the following Mean and SD of age of the subjects % of Male and Female subjects Correlations (Pearson r) between

Height and weight; PA and Height; PA and Weight t test (use independent t test) examining gender

difference in Height, weight, and PA

Copy and paste your SPSS outputs to a word document, then submit the hard copy to me