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**An introduction to data entry, data analysis, and graphing using SPSS**

Seminar 1 (2011) An introduction to data entry, data analysis, and graphing using SPSS

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**Statistical Package for the Social Sciences**

What is SPSS? Statistical Package for the Social Sciences A commonly used computer package in business, government, research and academic organizations. It is especially used in the social and behavioural sciences for processing and analysing data and for producing graphs.

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In this session Learn how to navigate through the different windows of SPSS Learn how to open and save data files Learn how to calculate simple statistics from variables in a data file Learn how to calculate new variables using the COMPUTE function Learn how to compare different subsets and groups of data using the SPLIT FILE and SELECT CASES IF functions Learn how to produce and edit simple graphs in SPSS and incorporate them into a word document

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Seminar Worksheets During the seminar you will have worksheets to complete. When you complete the worksheet enter your answers on the online worksheet which is on the U24103 resources page. On Friday you will receive a with your mark and the correct answers.

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**Why are Statistics important?**

They help put a number in its context* *if used correctly

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**Putting a number in its context January 8th, 2011 by Ben Goldacre in bad science**

The many Media outlets reported the story that 584 woman with the contraceptive implant had unplanned pregnancies. MHRA estimate that million implants have been sold. Each implant lasts 3 years, this gives a total exposure time of 4.06 million women-years at risk. 584 unplanned pregnancies in this exposed population means there were 1.4 unwanted pregnancies reported for every 10,000 women with implants per year. Or, you can say that the failure rate is 0.014% per year. This is rather good: Implants are still the most reliable form of contraception 4,065,000 to 10, 000 which you do by dividing by Then divide the 584 pregnancies by which gives 1.43. To get the percentage you divide 1.43 by 100 which gives 0.014%

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**Implants are still the most reliable form of Contraception**

The headline: Is a lot less scary when the number 584 it is put in context: The failure rate for the contraceptive implant is 0.014% per 10,000 per year Or without numbers: Implants are still the most reliable form of Contraception Back to SPSS

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**SPSS version 19 interface**

Where to find help File menu. Here is where you load and save files. Current ‘active’ data-entry cell Switch between “Data view” & “Variable view”

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**A sample of 50 people asked to answer a set of questions for a survey of health behaviour.**

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**How to open an SPSS data file**

Select your file in the “Open Data” window File menu: Open: Data U:\data U Seminar 1 SurveyData_Seminar1

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**The SPSS ‘Data View’ window**

Each column represents a different variable Each row represents a different participant

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**Each column represents a different property of that variable**

The SPSS ‘Variable View’ This is where you tell SPSS what kinds of variables you have “Values” You can assign labels for each value of a variable. E.g. Male = 1, Female=0. Each row represents a different variable (column in the data view) Label is where you can give your variable a longer name “Type” property: what is contained in the variable: Numeric = Numbers String = Text Each column represents a different property of that variable Name is where you give your variable/column a short name. Remember you cannot use a space so you need to use a “_” “Measure” property: what is the ‘level of measurement’ in the variable Nominal, Ordinal, or Scale (i.e. interval or ratio) Roles What the variables role is Input = independent variable (IV). Target = dependent variable (DV). Both= ether IV or DV None. The variable has no role assignment. Partition. used to partition the data into separate samples. If you are missing a some data you should not just leave the cell blank. You should decide on a number and tell SPSS what it is in this box. People commonly use “666” or “999”

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**Orienting through SPSS menu options**

Data menu SPLIT FILE function (and other functions relating to selecting/ ordering data based on criteria) Analyse menu DESCRIPTIVES function (and all other functions relating to ANALYSIS of DATA) Graph menu Bar Chart function (and other graph-related functions) Transform menu COMPUTE function (and all other functions relating to modifying values and producing new variables from your data) Click here to see any names you have given to numbers in the Values

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**Click on these to navigate to the output from previous analyses**

The SPSS OUTPUT window Do not close this window keep the same window open for the whole session Where the data file is saved Print out of what you told SPSS to do Click on these to navigate to the output from previous analyses Use: “–” to hide things & “+” to show them again Output from an analysis

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**Generating simple descriptive statistics in SPSS**

SPSS can generate a multitude of statistics. We will not be using all of them in this course. Analyse menu DESCRIPTIVES (and all other functions relating to ANALYSIS of DATA) Today we are using Descriptive Statistics to look at the variables in your data, measures of central tendency, measures of dispersion etc

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**“Frequencies” function**

“Descriptives” function “Frequencies” and “Descriptives” have a lot of overlapping functions (e.g. both can give means, standard deviations). Frequencies has a greater range of options (e.g. it can also compute medians, modes).

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**Left hand box contains all the numerical variables in your data set**

Descriptives “Options…”: This gives some options for the type of statistics you wish to show. Left hand box contains all the numerical variables in your data set Put the variables that you want to compute statistics from by selecting them and clicking this arrow to move them into the right hand side box. Click on “Range” tick-box so you also get this statistic in your output

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**The OUTPUT window for Descriptives**

Q1: Find out the means and ranges of the heights and weights of the participants using the ‘Descriptives’ command. Number of participants The columns show the calculated values for each of the statistical measures you ask for Each row designates one of your variables.

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Frequencies The “Statistics…” option gives output options for ‘Frequences’ Options for ‘median’ and ‘mode’ Options for ‘Standard deviation’ and ‘standard error’ To select multiple items in a row click on the first item you want then hold down the “shift” key and click on the last one you want If checked ‘Frequencies’ outputs a list of occurrences of a particular value (useful for categorical and ordinal variables)

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**Q2: Use ‘Frequencies’ to find out **

a) How many males took part in the survey? b) To calculate what percentage of the sample are ‘Skilled labourers’ c)To find the median weight of the sample Frequencies table. e.g. for the ‘Cigarettes’ variable it tells you how many (and what percentage) of your data file are Smokers. Each column designates a separate variable. The different calculated values for that variable are shown on the individual rows.

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**How to produce new variables from values in a data-file**

SPSS allows us to calculate new variables based on combining the variables we already have in our file. For example, Body Mass Index (BMI) is a measure which is mathematically derived from a persons height and weight. Formula for BMI BMI is an (indirect) indicator of the proportion of body fat a person has and is thus a useful health measure.

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**The Compute function Transform menu COMPUTE function**

(and all other functions relating to modifying values and producing new variables from your data)

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**Type a valid mathematical formula to calculate the variable here.**

Enter the Target variable name here. This is the name that SPSS will give the new calculated variable. Note that spaces and certain characters aren’t allowed in variable names (e.g. symbols such as ‘&’). The “Label” option box below it allows you to specify things like the level of measurement etc. of the variable. Type a valid mathematical formula to calculate the variable here. If you wish to use existing variables then these can be moved in using the arrow from the horizontal variable box on the left.

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**We want to calculate BMI**

To do this we need peoples weight in metric Kilograms rather than imperial pounds (lb). The formula to do this is: kg = lb ÷ 2.2 First type a name for the new variable here: e.g. Weight_in_kg (**don’t use an existing variable name otherwise it will be overwritten**). To calculate the Weight in pounds we need the data variable for the weight in Kg. The conversion formula then requires us to divide this variable’s values by 2.2.

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**Weight_In_Kg = Weight_In_Lb / 2.2**

(N.B. for computers the * is a multiplication sign and the / is the division sign). What we are telling SPSS to do the sum: Weight_In_Kg = Weight_In_Lb / 2.2 Press and SPSS will now create and compute this new variable based on the formula you have given it.

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**Q3: Now you know how to use ‘Compute’ try to create a variable for BMI**

Q3: Now you know how to use ‘Compute’ try to create a variable for BMI. Remember the formula is: In the output window SPSS has printed out the sum you put into the compute window. In the data view window you should see that a new variable called Weight in kilograms has been calculated for each of the 50 participants in the sample.

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**Here are the BMI values for the first five participants (P00001 to P00005).**

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**How to analyse data groups in SPSS**

Often we are interested in looking at or comparing values of different groups within our data. For instance we might want to compare the average height of males and females. SPSS has several ways to allow us to do this. Data menu SPLIT FILE, SELECT CASES IF… function (and all other functions relating to selecting or ordering data based on given criteria) Or you can use the SPLIT FILE button

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**Change to ‘Compare groups’**

Split file function Change to ‘Compare groups’ If we want to compare Males and Females then move the ‘Gender’ variable to this box

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****When you have done this make sure you turn off Split file again**.**

Q4: Use ‘Split File’ to generate the mean heights of males and females in our sample. **When you have done this make sure you turn off Split file again**. Note that in the bottom-right corner of the SPSS data window it informs you that the file is now split by gender. This remains the case until you turn this off again in the ‘Split File’ function. Select : Now when you run any analysis again (e.g. Descriptives). You get separate values for Males and Females in the table.

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**Select Cases If.. function**

Sometimes we wish to include only a subset of the cases (participants) in our analysis. The ‘Select Cases If’ function allows us to include only a subset of cases (and ignore others) based on a criterion that we give it. Select “If condition is satisfied” Then press the IF button so we can enter our criterion.

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Criterion window. What we need to do here is enter a Boolean condition (i.e. a mathematical statement which is either True or False)

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**Gender = 0 greater than ‘>’ less than ‘<‘**

What this is telling SPSS is to select only those cases (participants) which have the Gender value of “0” (and therefore ignore all those that have the value 1). In other words - select only if the participant is ‘Female’ otherwise ignore Gender = 0 The is equal to sign ‘=‘ is a commonly used relation in Select Cases IF statements Others common signs for this function are: greater than ‘>’ less than ‘<‘ not equal to ‘<>’ (note Gender <> 1 would have the same effect here as Gender = 0)

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**P.S. How to remember ‘less than’ & ‘more than’?**

Pacman’s evil statistics-loving twin brother always eats the largest number P P .05 .05 So the p value is less than .05 or p<.05 So the p value is greater than .05 or p>.05

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**You can see that the male cases are temporarily crossed out.**

A new filter variable (called filter_$) is inserted “Filter On”

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If you now run any analysis with the filter ON the analysis will only be performed on the selected cases (others will be ignored in the calculation). Q5: Using Select Cases IF and the ‘Descriptives’ function, calculate the mean weight for people who drink less than 15 units of alcohol a week. **Remember to always turn off the filter after you finish with it in your analyses** Go back to the Select Cases IF menu and click on “Select all cases”.

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**Type your file name here**

You now have been shown the basics of data handling in SPSS. Now might be a good time to save a personal copy of the data file onto your personal folder (H:) or pen-drive. Type your file name here

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**We are going to stop for 20 min so you can work through Q6 & Q7 and have a break**

Q6: Answer the following questions using what you have learned (**Remember to take off Filter/Split File after use**) What is the mode average of sleep that participants in our sample have? What percentage of our sample are Students? Do males or of females have a larger standard deviation for BMI? What is the median hours of sleep that someone in a manual labour job reports they get? How many people in our sample are aged 35 or over? Who has a higher mean BMI in our sample, Smokers or non-smokers? Q7: Some more difficult questions (note that for these questions AND, OR, NOT can be used as well in Boolean conditions) How many people in our sample are both smokers and drink 15 or more units of alcohol per week? What is the mode average of units alcohol drank by someone who is over the age of 45 and is in either in a manual-labour, skilled labour, or administrative/clerical/sales job?

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**Q6: Answer the following questions using what you have learned **

What is the mode average of sleep that participants in our sample have? What percentage of our sample are Students? Do males or of females have a larger standard deviation for BMI? ...Females…. What is the median hours of sleep that someone in a manual labour job reports they get? How many people in our sample are aged 35 or over? Who has a higher mean BMI in our sample, Smokers or non-smokers? .. non-smokers..... Q7: Some more difficult questions) How many people in our sample are both smokers and drink 15 or more units of alcohol per week? ..6... What is the mode average of units alcohol drank by someone who is over the age of 45 and is in either in a manual-labour, skilled labour, or administrative/clerical/sales job? ... up to 14 units per week....

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**Using the graph functions**

SPSS can plot graphs from any of the data in your file. Graph menu All graph-related functions

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Histograms Are used to look at the distribution of data.

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**Here is an example for age**

Here is an example for age. This variable is clearly not very normally distributed. Q8: Create histograms for height, weight, BMI from the data file. Do these variables show a normal distribution?

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Bar chart Useful for comparing different participant groups on some measure. Requires two variables One usually ordinal or scalar for the Y axis. One categorical (for the x-axis)

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Y-axis variable (what values do you want the height of the individual columns to show) X-axis variable (what groups do you want the columns to represent) Select whether the height of the columns represents the mean, median or mode average (or some other measure) of the group.

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**Which of the different occupation groups has the lowest median BMI?**

An example SPSS bar chart showing a difference in height between the genders. Q9: Now produce a Bar graph showing the median BMI for the different occupation groups. Which of the different occupation groups has the lowest median BMI?

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**Scatterplot chart You can have different markers for different groups**

Useful for plotting the relationship between two interval (or ratio) level variables Need to give two variables: One for the x-axis and One for the y-axis You can have different markers for different groups

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**Edit it so it is easy to understand when printed in black and white**

Q10: Now produce an SPSS graph for height (Y axis) verses weight (X axis) where gender is distinguished with different markers. Edit it so it is easy to understand when printed in black and white Are the lines of best fit for males and females roughly parallel? Each point is an individual participant’s score on the two values. Double click on the graph to open chart editor

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**Right click on the finished chart. Copy the chart. Open Word**

Right click on the finished chart. Copy the chart. Open Word. Paste into word as a picture.

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**Self-study exercises for Seminar 1**

That’s all for today. Its worth spending a bit of time on your own using SPSS to really familiarise yourself with its functions. Try some exercises from the online book on the psychology resources page in the Statistics folder : Secure Resources SPSS Version 17 A Beginner's Guide to SPSS for Windows: Entering and Analysing Questionnaire data Using SPSS… Open the data file “spssraw.sav” this can be found at: u:\data\SOCSCI\spssraw.sav Have a look particularly at section 1. (pg. 1-6) Have a look at section 6. and section 7 (pg ) Have a look at section 10 (pg ).

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