PY4006 Practical worksheet Week 4

Study 1: The essentials!

IMPORTANT: Remember you MUST NOT copy and paste tables from SPSS into your lab report. THIS YEAR you MAY copy and paste the scatter plots into your lab report.

Part 1: setting up the analysis.

Fill in the below BEFORE analysing the Study 1 data…

The research question:

The design (including the variables):

The hypotheses:

Part 2: setting up your data file and examining your sample

Now, download and open the Excel sheet Study 1 data.xlsx from Moodle, Week 4.

You will see it is formatted in columns of Age, Gender, Preference, Positive Affect, Perceived coherence and Likelihood of Restoration. We will set up our SPSS file using these data.

1) Open the variable view in SPSS.

NOTE: NO spaces! SPSS doesn’t like them!

NOTE: NO spaces! SPSS doesn’t like them!2) Enter the name of your three variables – one variable per row.

Preference

PositiveAffect

PerceivedCoherence

LikelihoodRestoration

NB SPSS doesn’t like spaces, please use underscores (_) or abbreviate to something that makes sense to you!

Change the measure to ‘scale’.

3) Also add the demographic variables

Age (scale)

Gender (nominal) –you will need to assign the values for these, click the values”…”,

when the box pops up, set 1 as male by typing 1 in the value box, male in the Label box and then click Add.

Do the same for 2 as female and 3 as non-binary and 4 as prefer not to say

And then (and only then!) click OK

4) Go to data view and enter the data under your variable headings. Every participant gets one row.

Participant 1’s score for variable 1

Participant 1’s score for variable 2

NB. THIS IS ONLY SAMPLE DATA, NOT YOUR ACTUAL DATA!!

To get the information for your Participants section, we will want to know how many of each gender there are, and what the age range, mean age and SD of the age are.

Gender

Analyse Descriptive Statistics Frequencies

Put Gender into the variable(s) box.

How many males:

How many females:

How many other:

Ages

Analyse Descriptive Statistics Descriptives

Put Age into the variable(s) box.

What is the age range:

What is the mean age:

What is the SD of age:

Use your lab book. Fill in the Participants section.

Part 3: Describing and analysing the response data

The Results section is in two parts:

Descriptives statistics

Inferential statistics

1a) First, we will take a look at the data (descriptives): Click Analyse -> Descriptive Statistics and put the three variables of interest in the Variables box. (If you don’t remember how to do this, refer to last week’s practical!)

Now report:

Preference M = __, SD = __

Positive Affect M = __, SD = __

Perceived coherence M = __, SD = __

Likelihood of restoration M = __, SD = __

What can you say about these values?

1b) The scatterplots provide a good visualisation of the data. Create a scatterplot for each correlation you are interested in. Copy and paste the scatter plots here. Don’t forget you will need the axis labels and to provide a Figure number and legend BELOW the plot.

E.g. Copy and paste the plot of preference vs likelihood of restoration below:

Figure 1: scatter plot of preference and likelihood of restoration scores.

Now do the same for the others below-including the figure legend!

Use your lab book. Fill in the Descriptives section of the Results.

2) Now, we are going to see whether our hypotheses have been supported…or not…!!!

Run the correlations on the three variables, as in the practical from Week 3. See if you can remember how to do this, if not, you can look it up!

Using the output table, provide the statistics below for the correlations between:

Preference and Likelihood of Restoration:

r =

p =

df = ____You need to calculate this by hand! The degrees of freedom is calculated by the Number of participants in the sample, n – 2 =

What percentage of the variance in Likelihood of Restoration was explained by Preference? Calculate this by squaring the r value, and multiplying this by 100 to create a percentage, r2 =___________%

What percentage cannot be explained?____________

Positive Affect and Likelihood of Restoration:

r =

p =

df =

What percentage of the variance in Likelihood of Restoration was explained by Positive Affect? r2 =___________%

What percentage cannot be explained?____________

Perceived Coherence and Likelihood of Restoration:

r =

p =

df =

What percentage of the variance in Likelihood of Restoration was explained by Perceived Coherence? r2 =___________%

What percentage cannot be explained?____________

Write this in APA style:

There was a [significant/non-significant], [strong/moderate/weak], [positive/negative] correlation between [variable 1] and [variable 2], r (d.f)= [test statistic], p = [significance]. …% of the variance in [variable 1] was accounted for by the [variable 2]

Use your lab book. Fill in the Inferentials section of the Results.

Interpretation of the Results: So, what did you find?

For each (of the three!) correlation answer the below.

The two variables were:

Was it statistically significant?

How strong was the correlation?

What was the percentage variance that could be explained?

Implication of the Results: What can you do with these results? Any applications? How have they contributed to the previous research on this topic and to future questions?

Now, you can write your title :

Extra: How do they compare to the literature you cited in the Introduction?

Now, save this word document and keep it somewhere so that you can use it for your write up!

Export your SPSS output so that you can check it without having to use/install SPSS!

From your output file, Click File -> Export

From the drop-down select pdf format (or others if you prefer!) and then Browse to somewhere that you will remember to locate the file again! Then click ‘OK’

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