Calculate the mean, mode, median, standard deviation, variance, standard error of the mean, minimum, maximum, quartiles

INSTRUCTIONS TO CANDIDATES

ANSWER ALL QUESTIONS

Objectives: practice with the following:

1. How to open a data file in SPSS

2. How to find the variables in the data set in SPSS

3. How to analyze data in SPSS to do the following:

a. Descriptive statistics --- frequencies for categorical variables (nominal, ordinal)

i. Calculate count, percent, cumulative percent

b. Descriptive statistics --- frequencies with continuous variables (ratio, interval)

i. Calculate the mean, mode, median, standard deviation, variance, standard error of the mean, minimum, maximum, quartiles

ii. Chart = Histogram with normal curve on histogram

c. Correlation

d. Compare means between two groups – INDEPENDENT T-TEST

e. Compare means between three groups – ANALYSIS OF VARIANCE (ANOVA) 

f. Relationship between two categorical variables using cross-tabs and Chi Square test

g. Non-parametric tests: comparison of two groups and comparison of 3 or more groups

h. Linear regressions (simple and multiple)

i. Logistic regressions (simple and multiple)

4. How to do graph in SPSS (box plot, and scatter plot)

DETAILED INSTRUCTIONS:

• Open SPSS

• Click on “file” on the top left side of the screen

• Click on “open”

• Click on “data”

Select the sample data I sent from your computer “CKDATA150.SAV”

1. DESCRIPTIVE STATISTICS:

• Once the data is open, look at the bottom left side of the screen and click on “variable view” to see the variable names, labels, and value labels.

• Click on “data view” on the bottom left side of the screen

• Click on “Analyze” - descriptive statistics  frequencies  variable: gender, race, heartdisease, 

• Click “ok”

• Click on “Analyze” - descriptive statistics  frequencies  variable: AGE, CK, EDU, BMI, systolic_BP, FBG, creatine_kinase_N, fasting_glucose_N

• Click “statistics” -> mean, median, mode, minimum, maximum, quartiles, std deviation, SE mean

• Click “Charts”  “Histogram”  “show normal curve on Histogram”

2. CORRELATION

• Click on “Analyze” - correlate  bivariateCK, AGE, BMI, systolic_BP, FBG

 Correlation coefficient: select “Pearson”  test of significance: select “two-tailed”  click “ok”

3. T-TEST

• Click on “Analyze” - compare means  independent sample t-test test variables: creatine_kinase_N ; grouping variables: gender - define groups: 1 and 2  - continue -- ok

• Click on “Analyze” - compare means  independent sample t-test test variables: fasting_glucose_N;  grouping variables: gender - define groups: 1 and 2  - continue -- ok

4. ANALYSIS OF VARIANCE (ANOVA)

• Click on “Analyze” - compare means  ONE WAY ANOVA dependent list: creatine_kinase_N ; factor: RACE - OPTIONS: DESCRIPTIVE  - continue -- ok

• Click on “Analyze” - compare means  ONE WAY ANOVA dependent list fasting_glucose_N ; factor: RACE - OPTIONS: DESCRIPTIVE  - continue -- ok

5. CROSS-TABLES (CHI square)

• Click on “Analyze” - descriptive statistics  crosstabsrow=”GENDER”  column=”heartdisease” 

 Statistics: select “Chi Square”  click “ok”

• Click on “Analyze” - descriptive statistics  crosstabsrow=”RACE”  column=”heartdisease” 

 Statistics: select “Chi Square”  click “ok”

 

6. BOX PLOT

• Click on “graph” - legacy dialogs - box plot  simple  summaries of separate variables  define  box represent=creatine_kinase_N  

 

• Click on “graph” - legacy dialogs - scatter/dot  simple scatter  define  y-axis=creatine_kinase_N  x-axis=AGE   title: relationship between CK AND AGE IN YEARS”  click “ok” 

7. Nonparametric Tests:

Nonparametric tests make minimal assumptions about the underlying distribution of the data. 

Analyze   Nonparametric Tests  Independent Samples - click on objective [Automatically compare distributions across groups]. Click on “Fields” --> test fields [BMI], Groups [gender] - Settings [Mann-Whitney U test]

Analyze   Nonparametric Tests  Independent Samples - click on objective [Automatically compare distributions across groups]. Click on “Fields” --> test fields [systolic_BP], Groups [gender] - Settings [Mann-Whitney U test]

Analyze   Nonparametric Tests  Independent Samples - click on objective [Automatically compare distributions across groups]. Click on “Fields” --> test fields [BMI], Groups [race/ethnicity] - Settings [Kruskal-Wallis]

Analyze   Nonparametric Tests  Independent Samples - click on objective [Automatically compare distributions across groups]. Click on “Fields” --> test fields [systolic_BP], Groups [race/ethnicity] - Settings [Kruskal-Wallis]

 

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