Download - SPSS for Beginners

Entering data, calculating descriptive

statistics and exploring your data using SPSS

Dr. Christine Gregory

November 2010

• Open SPSS

• Open, import and save data files

• Defining variables

• Summarising data

– Descriptive statistics– Descriptive statistics

– Chart builder

• What else can SPSS do?

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Opening SPSS 15.0Always open SPSS first, then open or type in data.

Choose ONE

Open a data file from

SPSS OR Excel

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Open existing data

Opening data in SPSS 15.0

Open existing data

from the File menu.

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Output File• Shows output for ALL analysis run in SPSS

• Keeps a log of all activity of open data files

• Saved with the extension .spo

Everything done in SPSS is

shown here, in outline form.

A data file was saved as test.sav.

This was recorded in the log here.

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Saving your SPSS files• Save in one of YOUR folders

• Name file appropriately

• Choose correct file extension

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Save as type:.sav for data files

.spo for output files

Importing data from Excel

• The file MUST BE .xls NOT .xlsx

• Variable names CAN be imported too

• Must be in row 1 of the worksheet

• Must begin with a letter

• No spaces and no special characters (except _ )

• Data will appear in SPSS data editor

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For Example. Importing data from Excel.

Variable names(Row 1)

Filename (.xls)

Sheet1 contains the dataset

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Filename (.xls)

Select All Files

to see your .xls

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Tick here if

variable names

are in row 1.

Is this range correct?

If NOT

Enter correct range here

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Variable names(from Row 1)

View all data


View and define

variables

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SPSS Data Editor: Variable ViewView and define variables

Variable name

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If numeric...


Describe the

variable

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Width of column

in data view

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Alignment of

data entries in

data view

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Classify

variable type

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SPSS Data Editor: Data ViewView, enter or change data entries

Menu Bar

Tool Bar

Choose your view:Choose your view:

Numerical values

OR

Value labels

SUMMARISING DATASUMMARISING DATARepresenting data Diagrammatically & Numerically

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Levels of MeasurementData

CategoricalQualitative

ScaleQuantitative

Nominal(Unranked categories)

Ordinal(Ranked categories)

Discrete(Not possible to take

Continuous(Possible to take

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(Unranked categories)

� Marital Status

� Political Party

� Eye Color

(Ranked categories)

� Satisfaction level

� Level of agreement

(Not possible to take

fractional values)

� No. of cars

� No. of students

(Possible to take

fractional values)

� Height

� Weight

• In SPSS, data is either Nominal, Ordinal or Scale.

• It is essential to classify data correctly in SPSS.- Incorrect classification will result in incorrect analyses.

Summarising Variables Graphically

Categorical

1 Variablee.g., Gender

2 Variablese.g., Satisfaction rating

Categorical – Nominal or Ordinal

e.g., Gender e.g., Satisfaction rating

by Gender

Simple Bar Chart

OR

Pie Chart

Clustered Bar Chart

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Summarising Variables Graphically

Quantitative

1 Variablee.g., Gross Annual Income

Quantitative

by

Categorical

Quantitative – Scale

2 or more related

Variablese.g., Holding breath, Categorical

e.g., Gross Annual Income by

Gender

Histogram

1-D Boxplot

Stem & Leaf Plot

Simple Boxplot

Population Pyramid

Bar Chart of Means

Clustered Boxplot

e.g., Holding breath,

drinking water, gargling,

spoon of sugar.Related: the same group of

participants tried all 4 methods to

get rid of hiccups.

Bar Chart

of Means

Summarising Variables Numerically

Categorical

1 Variablee.g., Gender

2 Variablese.g., Satisfaction rating

Categorical – Nominal or Ordinal

e.g., Gender e.g., Satisfaction rating

by Gender

Frequency table

Mode and/or Medianuse Frequencies in SPSS

Contingency tableuse Crosstabs in SPSS

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Summarising Variables Numerically

Quantitative

1 Variablee.g., Gross Annual Income

Quantitative

by

Categorical

Quantitative – Scale

Categoricale.g., Gross Annual Income by

Gender

Descriptive Statsuse Frequencies or

Descriptive Statistics in SPSS

Descriptive Statsuse Explore in SPSS

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DESCRIPTIVE STATISTICSDESCRIPTIVE STATISTICSDescribing and presenting data using SPSS

Download “employ.sav” from the ASK section on U-Link to carry out several of the

analysis shown in the remainder o the presentation.

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Descriptive Statistics Menu

Statistics

Charts• Bar

• Pie

• Histogram

Frequency tablesFrequency tables

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Limited statistics• Mean, SE of Mean

• Stdev, Variance

• Range, Min, Max

• Skewness, Kurtosis

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Statistics

Plots• Boxplots

• Stem-and-leaf

• Histogram

• Normality plots• Normality plots

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Contingency table(Counts or %’s)

•Observed tallies

• Expected tallies

Crosstab statistics• Chi-square• Chi-square

• Correlations

Clustered bar charts

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Frequencies. Multiple scale and/or categorical variables.

ONLY

appropriate for

categorical variables

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Frequencies Output. Ethnic group and Job Satisfaction Scale 1

• ONLY a frequency table was outputted.

• Did not request statistics for these categorical variablesEthnic Group

36 51.4 51.4 51.4

18 25.7 25.7 77.1

14 20.0 20.0 97.1

2 2.9 2.9 100.0

70 100.0 100.0

White/European

Asian

West Indian

African

Total

ValidFrequency Percent Valid Percent

Cumulative

Percent

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70 100.0 100.0

Job Satisfaction Scale - Item 1

7 10.0 10.3 10.3

22 31.4 32.4 42.6

24 34.3 35.3 77.9

13 18.6 19.1 97.1

2 2.9 2.9 100.0

68 97.1 100.0

2 2.9

70 100.0

Strongly Disagree

Disagree

Undecided

Agree

Strongly Agree

Total

Valid

0Missing

Total

Frequency Percent Valid Percent

Cumulative

Percent

Total A

Total B

Percent = (Frequency)/(Total B)Valid Percent = (Frequency)/(Total A)

• Descriptive statistics

• Histogram with normal curve overlay.

Frequencies Output. Gross Annual Income

Statistics

Gross Annual Income

68

2

7819.12

7800.00

6800a

997.947

995897.7

.370

Valid

Missing

N

Mean

Median

Mode

Std. Deviation

Variance

Skewness

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.291

-.294

.574

4600

5900

10500

6925.00

7800.00

8675.00

Std. Error of Skewness

Kurtosis

Std. Error of Kurtosis

Range

Minimum

Maximum

25

50

75

Percentiles

Multiple modes exist. The smallest value is showna.

Messages appear at the bottom

Q1Q2

Q3

(Quartiles)

Descriptives. Analyse scale variables.

• Appropriate for scale variables ONLY.

• Offers fewer statistics than Frequencies.

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Calculates the z-values for each

variable and saves as a new variable.

Descriptives Output. Gross annual income and Age last birthday

Standardised values

saved as variables:

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saved as variables:

Z-values for Gross

Annual Income and age

Explore. Examine each scale variable by each categorical variable.

Add 1 or more

scale variables here

Add 1 or more

categorical

variables here

Output

Statistics ONLY

Plots ONLY

or Both

Outputs most

descriptives

offered under

Frequencies

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variables here

K-S test for normality for

each group within each

Factor variable for each

Dependent variable

Explore Output. Exam Performance by Gender

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Explore Output. Exam Performance and Anxiety by Gender

Male and Female

together for each

Dependent

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Anxiety and

Performance together

for each Factor

Crosstabs. Ethnic group by Gender

Add 1 or more

categorical

variables for row

and column

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SPSS helps out by

identifying which

stats should be

used on certain

data types

Output

One crosstabs table

between each row

and column variable

Crosstabs Output. Ethnic group by Gender

Case Processing Summary

70 100.0% 0 .0% 70 100.0%Ethnic Group * Gender

N Percent N Percent N Percent

Valid Missing Total

Cases

Ethnic Group * Gender Crosstabulation

22 14 36

20.1 15.9 36.0

31.4% 20.0% 51.4%

Count

Expected Count

% of Total

White/EuropeanEthnic

Group

female male

Gender

Total Observed

Expected

% out of 70

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31.4% 20.0% 51.4%

8 10 18

10.0 8.0 18.0

11.4% 14.3% 25.7%

8 6 14

7.8 6.2 14.0

11.4% 8.6% 20.0%

1 1 2

1.1 .9 2.0

1.4% 1.4% 2.9%

39 31 70

39.0 31.0 70.0

55.7% 44.3% 100.0%

% of Total

Count

Expected Count

% of Total

Count

Expected Count

% of Total

Count

Expected Count

% of Total

Count

Expected Count

% of Total

Asian

West Indian

African

Total

% out of 70

CHART BUILDERCHART BUILDERRepresenting data graphically using SPSS

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Opening the Chart Builder• Select Chart Builder… from the Graphs menu

• Access Graphs from the Data Editor

– Data View OR Variable View

• OR Access Graphs from the Output window

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All variables

listed here

Select

chart type

Select

chart format

Build your

chart here

Start over!

Histograms• Simple. ONE continuous scale variable

• Stacked. ONE continuous scale variable split by ONE

categorical variable.

• Frequency Polygon. ONE continuous scale variable

• Population Pyramid. ONE continuous scale variable

split by ONE categorical variable.split by ONE categorical variable.

Simple Histogram Stacked Histogram

Frequency Polygon

Population Pyramid

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Simple Histogram. Gross Annual Income.

Choose Histogram from

properties window

Displaying the Normal

Curve is optional.

Drag scale variable here

e.g. Gross Annual Income

SPSS output

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Stacked Histogram. Gross Annual Income by Ethnic Group.

Choose Histogram from

properties window

Drag categorical variable here

e.g. Ethnic Group



SPSS output

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Stacked Histogram. Gross Annual Income by Gender.


e.g. Gender


e.g. Gross Annual Income SPSS output

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Boxplots• Simple: ONE scale variable split by ONE category.

• Clustered: ONE scale variable clustered by ONE

category and split by ONE category.

• 1-D: ONE scale variable.

Simple Boxplot 1-D Boxplot

Clustered Boxplot

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Simple Boxplot. Gross Annual Income by Ethnic Group.




e.g. Ethnic Group

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SPSS output

Clustered Boxplot.


e.g. Cluster by Gender

Gross Annual Income split by Ethnic Group & clustered by Gender.




e.g. Split by Ethnic Group

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SPSS output

1-D Boxplot. Employee Age Last Birthday.


e.g. Age Last Birthday

SPSS output

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Bar Charts• Simple.

– ONE categorical variable.

• Simple OR Simple Error.

– ONE scale variable split by ONE categorical variable.

– TWO OR MORE related scale variables (e.g. compare means).

Simple Bar Chart

Simple Error

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Simple Bar Chart. Gender.

Select Count from the

properties window

* No equivalent Simple Error Bar Chart.

SPSS outputDrag categorical variable here

e.g. Gender

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Simple Bar Chart. Cholesterol level by Smoke.* Same process for a Simple Error Bar Chart.


e.g. Cholesterol level(Select Mean from the properties window)

SPSS output


e.g. Smoke

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Simple Bar Chart. Methods for getting rid of hiccups.

Drag multiple scale variables heree.g. Breath, Drinking, Gargling and Sugar

(Select Mean from the properties window)

* Same process for a Simple Error Bar Chart.

SPSS output

Leave this empty. It will change

to INDEX after you choose Y.

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Bar Charts• Clustered OR Stacked.

– ONE categorical variable clustered by ONE categorical variable.

– ONE scale variable split by ONE categorical variable and

clustered by ONE categorical variable.

– TWO OR MORE scale variables clustered by ONE categorical

variable (e.g. compare means).

Stacked Bar Chart

Clustered Bar Chart

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Clustered Bar Chart.



Cholesterol level split by Smoke & clustered by Gender.


e.g. Cholesterol level(Select Mean from the properties window)

SPSS output


e.g. Split by Smoke

* Same process for a Stacked Bar Chart.ASK Week Fall 2010

Clustered Bar Chart. Hiccup methods clustered by Gender.



Drag multiple scale variables heree.g. Breath, Drinking, Gargling and Sugar

(Select Means from the properties window)

SPSS outputLeave this empty. It will change

to INDEX after you choose Y.

Error bars are optional

* Same process for a Stacked Bar Chart.ASK Week Fall 2010

Line Charts• Simple. Alternative to a Simple Bar Chart.

• Multiple. Alternative to a Clustered Bar Chart.

Multiple Line Chart

Simple Line Chart

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Pie Charts• Pie.

– ONE categorical variable (alternative to a Simple Bar Chart).

– ONE scale variable split by ONE categorical variable.

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Pie Chart. Ethnic Group.

Select Value from the

properties window

SPSS outputDrag categorical variable here

e.g. Ethnic Group

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Pie Chart. Gross Annual Income split by Ethnic Group.



SPSS output


e.g. Ethnic Group

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CAUTION: This representation can be misleading and misinterpreted if the count of each

ethnic group is not close in size (if not equal). Each piece represents the proportion of

the total gross annual income of the entire sample for each ethnic group. Thus, as most

participants were White/European, this group makes up the largest proportion.

Scatter Plot• Simple. ONE scale independent variable by ONE OR

MORE scale dependent variables.

• Grouped. ONE scale independent variable by ONE or

more scale dependent variables and split by ONE

categorical variable .

• Matrix. TWO OR MORE scale variables.

Simple Scatter Grouped ScatterSimple Scatter

Matrix Scatter

Grouped Scatter

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Simple Scatter. Exam Performance by Time Spent Revising.

Drag 1 or more scale variables heree.g. Exam Performance

* Could also use to create a time series.

SPSS output

Drag independent scale variable here

e.g. Time Spent Revising

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Grouped Scatter.

Drag 1 or more scale variables here

e.g. Exam Performance

Exam Performance by Time Spent Revising and split by Gender.


e.g. Split by Gender

SPSS output

Drag independent scale variable here

e.g. Time Spent Revising

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Matrix Scatter.Exam Performance, Exam Anxiety and Time Spent Revising

SPSS output

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Drag 2 or more scale variables here

e.g. Exam Performance, Exam Anxiety,

Time Spent Revising

WHAT ELSE…?WHAT ELSE…?A quick look at what else SPSS can do

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Quick list of common uses of SPSS• Correlation Coefficients

• Parametric & Nonparametric Hypothesis Tests

– T-tests

– Chi square tests

– ANOVA

– MANOVA– MANOVA

• Recode variables

• Transform variables

• Select special cases of a variable to analyse

• Generate random numbers (or samples)

• …and the list goes on…

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SPSS Course at University of Colorado at Colorado Springs:http://www.uccs.edu/~faculty/lbecker/SPSS/content.htm

SPSS Tutorials (lots of links on this site):http://www.uccs.edu/~faculty/lbecker/SPSS/content.htm

SPSS On-Line Training Workshops (tutorials & videos):http://calcnet.mth.cmich.edu/org/spss/toc.htm

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SPSS Survival Manual, 4th Edition (2010) by Julie Pallant.

(For SPSS Version 15 or later)

Discovering Statistics Using SPSS, 3rd Edition (2009) by Andy Field.

(For SPSS Version 15 or later)

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• Stats & SPSS drop-in (≈10 min).(If more time is needed we’ll make an appointment)

• Undergraduates:

Friday 12.00-13.00

ASK area, ground floor of libraryASK area, ground floor of library

• Post Graduates:

Thursdays 13.30-15.00

Graduate School Training Room

(it’s in with the offices on the top floor)

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THE ENDTHE END

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