basics of spss, part 1

Part 1: Getting started entering data and defining variables

» Purpose and use of SPSS

» Open SPSS

» What is a Variable?

» Defining variables in SPSS

» Entering Data

» Open and save data files

» Import data from Excel

» Handling missing data

ASK at Brunel (2014) 2

» SPSS is a Statistical Software Package

» SPSS is a tool

It only does what it’s ‘told’ to do.

It does not think for you

It is not a black box

» You need to know the correct statistics for your research BEFORE using SPSS.

» If you understand the statistics, then you are ready to do analysis in SPSS.

Click on the Windows Start Icon

Type SPSS 20 into the search box

Select SPSS 20 from the list

Open NEW data file

Enter variable names in the first column of Variable View.

Enter the data for each variable.

Each variable name will appear as a column heading replacing var.

What is a variable? How do we define variables in SPSS?

» A measurement:

A characteristic + E.g., Gender, Age, Height, Weight…

Time points + E.g., pre-test, post-test, T0, T1, T2…

Experimental Condition + E.g., Condition, Experimental group…

Opinion/belief + E.g., A survey question which asks for a respondent’s level of

agreement with a statement

Etc…

What is your gender?

Male or Female

How long does it take, on average, to commute into Uni?

What is your main mode of transport to Uni?

Indicate your level of agreement with this statement:

“Most days, my commute causes me to feel stressed when I arrive at university”.

» Random sample of 200 residents of Uxbridge.

» Asked respondents’ their view on stem cell research using a 3 pt. Likert Scale (Disagree, No Opinion, Agree).

» Asked respondents’ if they believed global warming was an important issue using a 5 pt. Likert Scale (Strongly Disagree to Strongly Agree).

Questionnaire Responses

» Random sample of 200 residents of Uxbridge.

» Asked respondents’ their view on stem cell research using a 3 pt. Likert Scale (Disagree, No Opinion, Agree).

» Asked respondents’ if they believed global warming was an important issue using a 5 pt. Likert Scale (Strongly Disagree to Strongly Agree).

Resident StemCell GlobalWarming

1 Agree Strongly Agree

2 Undecided Agree

3 Undecided Strongly Disagree

4 Disagree Undecided

… … …

Experimental Condition Cond 1 and 2 are independent,

NOT repeated measures.

Score on a test

» 30 participants were used to investigate the effect of caffeine on their ability to sleep.

» The 30 participants were randomly assigned to one of 2 conditions: No caffeine (control) or one dose of caffeine every 3 hours from 9am-6pm.

» The study measured participants ability to sleep by taking the average number of hours slept per night over a 2 week period.

Caffeine and Sleep

» 30 participants were used to investigate the effect of caffeine on their ability to sleep.

» The 30 participants were randomly assigned to one of 2 conditions: No caffeine (control) or one dose of caffeine every 3 hours from 9am-6pm.

» The study measured participants ability to sleep by taking the average number of hours slept per night over a 2 week period.

Caffeine and Sleep

Participant Condition AvgHoursSlept

1 Control 7.2

2 Caffeine 6.7

3 Caffeine 6.3

4 Control 6.9

… … …

Caffeine and Sleep

Status when admitted to care facility

Anxiety level measured at 3 time points for each participant

Why not enter TIME as 1 variable like we

did for STATUS?

» 50 participants of varying fitness levels were used to investigate whether personal trainers make a significant difference in ones fitness.

» Participants were randomly assigned to one of two training groups: self training or professional trainer.

» Each participants 1 mile time (in mins) was recorded 2 days prior to the start of the study.

» Each group then followed a specific training regime for 30 days and their 1 mile time (in mins) recorded again.

Fitness Regime

» 50 participants of varying fitness levels were used to investigate whether personal trainers make a significant difference in ones fitness.

» Participants were randomly assigned to one of two training groups: self training or professional trainer.

» Each participants 1 mile time (in mins) was recorded 2 days prior to the start of the study.

» Each group then followed a specific training regime for 30 days and their 1 mile time (in mins) recorded again.

Fitness Regime

Pre-test and Post-test

Fitness Regime

Participant Training Pre_Mile Post_Mile

1 Self 15.3 14.1

2 Professional 16.1 14.9

3 Self 20.5 16.8

4 Self 16.8 16.2

… … … …

Variables

Categorical Qualitative

Scale Quantitative

Nominal

(Unranked categories)

Marital Status

Political Party Eye Color

Ordinal

(Ranked categories)

Satisfaction level

Level of agreement

Not grouped Height

Weight

No. of cars

No. of students

• In SPSS, data is either Nominal, Ordinal or Scale. • It is essential to classify data correctly.

- Incorrect classification… may result in incorrect analyses.

Code categorical variables

Enter data

Level of Measurement?

Categorical variables need to be coded Scale variables do not need to be coded

0 = Male 1 = Female

Scale, does not need to be coded

1 = tfl (i.e. public transport) 2 = Car 3 = Cycle 4 = Walk

Indicate your level of agreement with the following statement:

“Most days, my commute causes me

to feel stressed when I arrive at university”.

1 = Strongly Disagree 2 = Disagree 3 = I don’t know 4 = Agree 5 = Strongly Agree

Data has been coded Now we’re ready to enter it in SPSS

1. Enter & define variables from Variable View.

• Variable names • Must begin with a letter • No spaces and no special characters (except _ )

• Type • Should (almost) always be numeric • SPSS cannot analyse non-numeric data

• Decimals • How many decimal places do you want to see in the Data View?

• Label • IMPORTANT!!! Make good labels! • Short description of the variable • This is what will be written on all graphs & tables

• Values (i.e., Value labels) • IMPORTANT!!! - Tell SPSS what all the codes represent! • This is what is written on all graphs & tables

• Missing • Missing data can be coded too • Chose a number not in the data, like 99 or 999 • Replace all missing values in your data with this code first

• Measure • Level of Measurement (Nominal, Ordinal, Scale) • By default ALL new variables are unknown • YOU must choose the appropriate measure

2. Enter data from Data View.

• Variable names • Will become column headings in Data View.

Now, let’s enter some data

Saving and Opening Data or Output Files

Locate a folder to save it in:

On your H drive OR On your pen drive

Name it appropriately Extension .sav

Everything done in SPSS is shown here,

in outline form.

Shows output for ALL analysis run in SPSS Keeps a log of all activity of open data files Saved with the extension .spv

A data file was saved as SPSS Workshop Example.sav and logged in the output file.

New data file

New output file

Existing data file

Existing output file

Importing data from Excel

Click here

Save this file to your H: drive

or pen drive

» Log onto Blackboard

» Go to the Organisation Academic Skills

» In the left column, under Workshop Presentations

Click on Statistics and SPSS

» Find the SPSS Workshop

Download the Excel File: “CommutingSurvey.xlsx”

» Save this file somewhere you can find it later.

» Do not open it. You cannot import the file if it’s open.

» Can be .xls OR .xlsx

» Variable names CAN be imported too

Must be in row 1 of the worksheet

They will be imported to the Variable View

» Data will appear in SPSS Data View

Variable names (Row 1)

Filename

(.xlsx)

This sheet contains the dataset

Existing data file

Choose Excel file type to see your .xlsx

Find the folder where you

saved the file Select the Excel file

Choose the correct

worksheet

View all data Dr.

Variable Names

(from Row 1)

This variable name from Excel could not be used. SPSS made it a label and

created a new variable name

How to handle missing data

» Any blank (i.e., missing) data is automatically considered missing by SPSS.

It will not be included in the analysis.

This means you DO NOT have to code missing data

» Why code missing values if you don’t have to?

Sometimes data accidently gets deleted. If missing values are coded then you know a blank space shouldn’t be there.

There is more than one reason data is missing and you want to distinguish between them.

+ E.g., A participant chose not to answer a survey question or question was not applicable to them – you may want to record these as different kinds of missing data.

There are 3 missing values for

TravelTimemin

• Replace missing values with a code • Use a code that will not occur for the variable • Let’s use -1, as negative time is not possible

Select the variable you

want to recode

Click here to recode the

variable

Enter the code as the new value

Click Add. MISSING -> -1

will appear here

Click Continue then Click OK

Missing values have been

replaced with -1 for TravelTimemin

Remember… From Variable View

Define the missing values 8

• Discrete (whole numbers) • Enter missing value codes used for the variable (e.g., -1) • Click OK

This is only a code – it tells SPSS what value(s) represent missing values. It does not replace missing values with the code for you!

» Variables go in columns

» Categorical data should be coded first

» If you import data from Excel, make sure to:

Put variable names in the first row

Code your categorical data first, then import codes

» If you choose to code missing data:

First, replace all missing values with the code

Second, define the missing value code in the Variable View

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

» SPSS Survival Manual, 5th Edition (2013) by Julie Pallant.

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

» Discovering Statistics Using SPSS, 4th Edition (2013) by Andy Field.

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