Reference no: EM13910649
Module code: 4PS046
Stage: 1 CW2: QUANTATIVE Portfolio of statistical exercises
Assesses Learning outcomes 3 & 4
Preamble
For the assignment you have been given brief background details of a research project and you are required to produce a portfolio of short reports. Portfolios are to be worked on individually and each of you will receive a unique set of data. To access your data you will need to click on the links from the web pages (see below) You will be asked for your user name (your student number) and then asked to choose a password; your data will then be generated.
You should analyse the dataset and report your findings in a format suitable for publication in a journal. You should include relevant SPSS printouts with your report. Inclusion of the SPSS output is a pass/fail element of the assignment
Note that the reports you will produce are very short, but they are designed to test your understanding and interpretation of statistical analyses.
Background Information
A developmental psychologist was interested in children's construction play and the factors which determined the ease with which children are able to construct models. He designed a study in which children were tested for Spatial Working Memory and then presented with a series of Lego models of varying complexity to build at age 8 and retested when they were 12 years old. Spatial Working Memory scores at age 8 were used to categorise the children as having either high or low spatial ability.
As the psychological literature suggests that there are sex differences in spatial ability he also noted the sex of each of his participants. During both Lego tasks all participants were presented with 8 models in random order, which were designed to be of varying difficulty and a mean time taken to assemble the models was calculated. Data were collected across a range of variables, some of which are presented here.
Sex: Male or Female
SWM8: Score on spatial working memory task aged 8
SWM12: Score on spatial working memory task aged 12
SpAb8: Participants designated as either high or low in spatial ability aged 8
MeanTim8: Mean time taken across all models aged 8
MeanTim12: Mean time taken across all models aged 12
THE DATA FOR THE ABOVE CAN BE FOUND BELOW:
For each of the following questions you should:
- Produce a testable hypothesis,
- Perform an appropriate statistical analysis
- Report the findings of your analysis in the correct format
- State what can be concluded from the analysis
Research Questions
- Is there any support for the idea that there are sex differences in high and low spatial ability at age 8?
- Is there any difference in the mean time taken by those of high and low spatial ability to build the Lego models when tested at age 8?
- Is there any difference in the mean time taken to build the Lego Models at age 8 and age 12?
- Is there a relationship between Spatial Working Memory scores at age 8 and Spatial Working Memory scores at age 12?
- Does Spatial Working Memory score at age 8 predict the mean time taken to build the Lego models at age 12?
DATA TO BE ANALYSED
80 individuals
Sex
|
SWM8
|
SWM12
|
SpAb8
|
MeanTime8
|
MeanTime12
|
Female
|
46
|
43
|
High
|
727
|
698
|
|
Male
|
44
|
53
|
High
|
819
|
804
|
|
Male
|
44
|
48
|
High
|
866
|
882
|
|
Male
|
31
|
28
|
Low
|
793
|
795
|
|
Male
|
33
|
28
|
Low
|
751
|
747
|
|
Male
|
36
|
44
|
Low
|
881
|
871
|
|
Male
|
44
|
42
|
High
|
821
|
803
|
|
Female
|
36
|
45
|
Low
|
864
|
856
|
|
Female
|
39
|
34
|
High
|
850
|
842
|
|
Male
|
31
|
28
|
Low
|
851
|
855
|
|
Female
|
30
|
39
|
Low
|
829
|
840
|
|
Male
|
30
|
29
|
Low
|
897
|
901
|
|
Male
|
48
|
52
|
High
|
736
|
737
|
|
Female
|
39
|
37
|
High
|
718
|
690
|
|
Female
|
45
|
46
|
High
|
769
|
740
|
|
Male
|
39
|
34
|
High
|
791
|
771
|
|
Female
|
39
|
47
|
High
|
708
|
682
|
|
Female
|
48
|
59
|
High
|
716
|
723
|
|
Female
|
36
|
41
|
Low
|
843
|
818
|
|
Male
|
42
|
43
|
High
|
836
|
849
|
|
Male
|
30
|
40
|
Low
|
820
|
811
|
|
Female
|
41
|
48
|
High
|
880
|
879
|
|
Female
|
35
|
42
|
Low
|
748
|
742
|
|
Female
|
40
|
52
|
High
|
710
|
707
|
|
Female
|
30
|
36
|
Low
|
779
|
749
|
|
Male
|
43
|
40
|
High
|
886
|
894
|
|
Female
|
32
|
36
|
Low
|
872
|
862
|
|
Male
|
33
|
44
|
Low
|
743
|
740
|
|
Male
|
42
|
39
|
High
|
859
|
840
|
|
Female
|
32
|
42
|
Low
|
797
|
785
|
|
Female
|
30
|
28
|
Low
|
848
|
839
|
|
Male
|
40
|
40
|
High
|
894
|
886
|
|
Female
|
36
|
48
|
Low
|
829
|
831
|
|
Female
|
48
|
53
|
High
|
771
|
752
|
|
Male
|
40
|
40
|
High
|
729
|
727
|
|
Male
|
40
|
52
|
High
|
892
|
889
|
|
Female
|
41
|
41
|
High
|
703
|
704
|
|
Female
|
36
|
38
|
Low
|
876
|
891
|
|
Female
|
32
|
34
|
Low
|
814
|
818
|
|
Male
|
36
|
34
|
Low
|
886
|
903
|
|
Female
|
35
|
45
|
Low
|
807
|
814
|
|
Female
|
33
|
30
|
Low
|
818
|
790
|
|
Female
|
41
|
53
|
High
|
890
|
901
|
|
Male
|
34
|
30
|
Low
|
791
|
780
|
|
Male
|
46
|
56
|
High
|
794
|
781
|
|
Male
|
34
|
30
|
Low
|
873
|
859
|
|
Female
|
43
|
50
|
High
|
747
|
731
|
|
Male
|
40
|
42
|
High
|
732
|
741
|
|
Female
|
37
|
38
|
High
|
778
|
783
|
|
Male
|
47
|
45
|
High
|
769
|
773
|
|
Female
|
48
|
43
|
High
|
788
|
798
|
|
Male
|
38
|
40
|
High
|
808
|
795
|
|
Male
|
30
|
29
|
Low
|
893
|
873
|
|
Male
|
35
|
32
|
Low
|
824
|
796
|
|
Female
|
34
|
42
|
Low
|
746
|
743
|
|
Male
|
46
|
49
|
High
|
766
|
766
|
|
Female
|
30
|
27
|
Low
|
712
|
728
|
|
Female
|
32
|
38
|
Low
|
842
|
819
|
|
Male
|
47
|
44
|
High
|
856
|
866
|
|
Male
|
37
|
43
|
High
|
899
|
918
|
|
Female
|
44
|
52
|
High
|
711
|
685
|
|
Female
|
37
|
39
|
High
|
724
|
719
|
|
Female
|
40
|
37
|
High
|
724
|
696
|
|
Male
|
38
|
42
|
High
|
733
|
736
|
|
Male
|
33
|
31
|
Low
|
790
|
773
|
|
Female
|
35
|
33
|
Low
|
889
|
876
|
|
Female
|
46
|
43
|
High
|
751
|
745
|
|
Male
|
32
|
28
|
Low
|
732
|
749
|
|
Male
|
35
|
46
|
Low
|
880
|
851
|
|
Female
|
38
|
37
|
High
|
720
|
739
|
|
Male
|
30
|
29
|
Low
|
727
|
717
|
|
Female
|
34
|
30
|
Low
|
723
|
743
|
|
Male
|
43
|
39
|
High
|
766
|
784
|
|
Female
|
31
|
36
|
Low
|
815
|
807
|
|
Male
|
41
|
47
|
High
|
709
|
725
|
|
Female
|
44
|
51
|
High
|
874
|
855
|
|
Male
|
46
|
43
|
High
|
777
|
795
|
|
Female
|
35
|
40
|
Low
|
765
|
755
|
|
Male
|
37
|
45
|
High
|
853
|
836
|
|
Male
|
33
|
34
|
Low
|
893
|
870
|
|
Machine and determines
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