Measurement Details and Further Reading Resources

Part 1 of this assessment item is a partial research report

You are provided with a synopsis (i.e., outline) of a research scenario that includes information that can be translated for the Method section. You are also provided with the data collected in the study.

Your task is to write the last paragraph of the Introduction, complete the Method section, write the Results section, and also the first paragraph of the Discussion section. To complete this task successfully there will be data entry and the appropriate statistical technique and interpretation of results to perform. This is explained further below.

Part 2 of this assessment item is to identify any potential flaws with the research design. Further details provided below.

Parts 1 and 2 comprise approximately 1000 words of the 1500 word total for Assessment 1.

Part 3 of this assessment provides you with a second research synopsis. You are required to answer additional questions in relation to the experimental design. More information below.

Part 3 comprises approximately 500 words of the 1500 word total for Assessment 1.



Submission of Assessment 1 (all three parts) is through Turnitin see vUWS and your learning Guide for further information. The Turnitin Link will be in your Assessment Folder.




Part 1

Partial Research Report


The local area school directorate (LASD) has become concerned over the attrition rates for high schools in the area. Much research has been published in the US about the risk factors related to high school drop out rates, so the LASD has decided to conduct a pilot study (a small initial study) to determine if these risk factors are present in New South Wales High Schools as well.

If these risk factors are present, they may be responsible for the recent increase in dropout rates. The good news however from the point of view of the LASD is that most of the risk factors identified by the research can be ameliorated or avoided – but first they must be identified.

The US research identifies the following risk factors as related to increased rates of dropping out of high school

  • Low Perceived Quality of School
  • Low Caregiver Engagement with School
  • Low Grades
  • Absenteeism


Following the research designs of the US studies, the LASD plans to calculate an mean OVERALL risk factor score for each of the two participating schools. These overall risk factor scores will be correlated with drop out rates in a later study.

Two high schools from the local area are chosen to participate in the initial study and just as luck would have it the chosen schools are Summertown High and Winterfield Grammar. This sends Principal Foster into a spin – she certainly doesn’t want her school to have a significantly higher overall risk factor than her nemesis Principal Fortescue’s school – Winterfield Grammar!

On receiving the news that Summertown High will be part of the pilot study, Principal Foster quickly logs into PsychInfo to search for journal articles regarding high school drop out risk factors in an attempt to see if she can somehow predict the outcome of this initial study by the LASD. Her preliminary readings confirm the LASD’s research measures – the risk factors the LASD identified are indeed associated in the literature with increased drop out rates.

Principal Foster thinks quickly about how her students may rate on the risk factors. Firstly, the successes of the drama students and wrestling team surely would have increased morale and good will towards the school – wouldn’t they? Secondly, being a performing arts high school, there are a myriad of practical and vocational classes. Thirdly, the significant adults and caregivers in the students’ lives are very proactive within the school – helping in the canteen, making sets and costumes etc., that’s got to indicate high levels of engagement.


Principal Foster is beginning to grow in confidence and quickly returns to her research. Principal Foster identifies another three risk factors strongly associated with high school drop out rates that the LASD did not include in their study variables. These are, gender (males have higher drop out rates than females); low involvement in extra curricular activities; and affinity with the high school attended (E.g., whether the high school is attended by default because it is the local high school, whether the high school was chosen by a significant adult, or chosen by the student themselves as a school that meets their requirements/fulfils an interest).

Based on her research and the scores required by the LASD, Principle Foster is confident that the Summertown High students will not have a higher overall total risk factor score than Winterfield Grammar.

With renewed enthusiasm, Principal Foster sets out to administer the tests required by the LASD to calculate an overall risk factor score.  The LASD provide her and Principal Fortescue with the following information;

At the end of the 2016 School Year

  1. Randomly select 24 Year 9 students to participate.
  2. Administer the Perceived Quality of School Scale (scored out of 100) and then the Caregiver Engagement Inventory (scored out of 100).
  3. Calculate overall grade percentage for each student in the sample based on final exam results across all subjects for the 2016 School Year (out of /100).
  4. Calculate the percentage of days each student in the sample was absent for the 2016 School Year (out of /100)
  5. Calculate each student’s Overall Risk Factor Score (out of /100).




For Part 1, your task is to create a directional hypothesis from the Research Scenario provided. That is, come up with the research question (directional) that you think Principal Foster’s research and theorising would predict.


Write only the following subsections of your report using APA 6th edition formatting:


  1. Title

Make up an appropriate title here.  It is not marked, but certainly worthwhile to focus your thoughts on the topic as it should contain the major variables you are investigating. Additionally, an appropriately formatted APA Title page is good practice for your professional papers.

  1. The last paragraph of the introduction (Approximately 100 words)

Hint:  Think of the kind of statement you might want to make at the end of a long Introduction, before leading into the Method and Results.  It is a statement that will explain to the reader the purpose of the study and what the literature (normally presented in an introduction) predicts. You can glean this information from Principal Foster’s thoughts on the risk factors and her proposed outcome.  The criteria provide specific information about what to include.

  1. The participants, materials and design, procedure sections of the Method (Approximately 300 words in total). DO NOT simply copy and paste the scenario into your assignment – you’ll need to write about the participant, design, materials, and procedure sections in your own words (they’re spelled-out in the scenario, so you don’t need to make anything up yourself). The materials section simply needs to provide information on any materials need to operationalise (measure) your variables and information can be found in the Measurements Document in this folder. The criteria also provides good guidance.
  2. The entire Results section (No more than 200 words).

You will need to either enter by hand, or copy and paste the data below into SPSS. HINT: Some manipulation of the data is required in order to measure the main variables of interest.

You will then need to determine the appropriate analytic technique for testing your hypothesis. In otherwords, you need to decide what test you will use.

Once you determine the appropriate test, you will run this analysis using SPSS and generate a set of statistics to achieve a probability (significance) level that either confirms or disagrees with your research hypothesis.

You will then use your Hills (2011) text as a template/guide to write up the results of your analysis including the appropriate statistical data and screening procedures. This section also needs to adhere to APA 6th edition protocols.

Appropriate and relevant SPSS output should be included as an Appendix and NOT DUMPED IN THE BODY OF YOUR RESULT SECTION. Any figures or tables you may wish to include in the body of the Result section must adhere to APA protocols.

The marking criteria also provides good guidance on what is required in this section.


  1. The first paragraphs of the Discussion section (Approximately 100 words).

Hint:  Think of the type of opening statement you might want to make at the beginning of the Discussion, before launching into the implications of the results.  You can consult any psychology research article for an idea of what to write here.  The marking criteria provides more detail.

NOTE: NO references are required for this assessment item

See the marking criteria attached to your Learning Guide on vUWS for the awarding of marks in this assessment.

The data are on the next page;



Student Age Gender Perceived Quality


Caregiver Involvement


Overall Grade




Overall Risk Factor


1 14 M 89 55 60 7  
2 14 M 55 50 60 0  
3 14 F 83 77 86 5  
4 15 F 63 59 70 10  
5 15 F 12 15 20 4  
6 14 F 66 85 78 4  
7 15 M 85 63 70 6  
8 14 F 73 57 70 8  
9 15 M 52 57 47 11  
10 15 F 74 62 50 5  
11 15 M 43 75 78 6  
12 14 M 81 70 82 15  
13 14 F 75 81 79 22  
14 15 F 80 87 86 6  
15 15 M 66 84 79 8  
16 15 F 87 81 75 4  
17 14 M 78 62 65 0  
18 14 F 56 67 60 7  
19 14 F 51 70 75 7  
20 14 F 75 91 76 9  
21 14 M 79 66 66 9  
22 14 F 70 81 75 4  
23 15 F 80 66 60 7  
24 15 F 79 66 66 0  



Student Age Gender Perceived Quality


Caregiver Involvement


Overall Grade




Overall Risk Factor


1 15 M 80 85 81 15  
2 14 M 58 60 66 5  
3 14 F 64 67 71 5  
4 14 M 50 55 37 6  
5 14 F 69 79 82 12  
6 15 M 79 59 61 14  
7 14 F 87 85 79 0  
8 14 M 73 74 78 5  
9 14 F 74 74 80 12  
10 15 M 80 84 77 7  
11 15 M 71 62 72 6  
12 14 F 75 75 81 8  
13 14 M 76 83 88 6  
14 15 M 69 81 62 9  
15 15 M 82 61 74 8  
16 14 M 96 89 78 7  
17 14 F 80 65 69 7  
18 14 M 41 45 50 6  
19 15 M 87 87 90 2  
20 14 F 80 66 66 4  
21 14 F 64 68 57 4  
22 14 M 80 91 88 5  
23 15 M 70 87 81 4  
24 14 M 56 66 60 8  





Part 2

Design Flaws

Identify potential design flaws and/or problems with the procedure that might affect interpretation of the results – at least four issues should be highlighted. You should go beyond issues of sample size and focus on issues with the study that may result in interpretation errors (drawing incorrect conclusions) or testing errors (producing an incorrect result or data that is unreliable).


HINT: Think deeply about how we tested our hypothesis – did our design allow us to answer our research question fully? Also, look at the procedure and how we manipulated our variables, were there any problems? Don’t necessarily limit yourself to only four issues if you can identify more, but four major issues are likely to score more marks than six minor issues.  Write in full paragraphs rather than ‘dot points’. 

(Approximately 300 words)

See the marking criteria for the awarding of marks in this Part and further details on Part 2.





Part 3

Design Effects

Part 3 Scenario

Mr Boris who teaches the Chemical Special Effects for the Theatre class (and has been teaching at Summertown High for 30 years), is tired of the chemical spills and explosions that keep happening in his classes. They are getting so bad that next year Principal Foster has threatened to deduct the cost of replacing any more equipment directly from his wages.  Further, Mr Boris is tired of parents complaining that they have to buy yet another school jumper because there are burn holes in the current one!

Mr Boris already has a topic called Knowledge of Burn Treatment and Evacuation Procedures but it seems the students forget what to do when incidents occur or perhaps cannot remember the chemical compounds likely to result in small explosions or fires? Mr Boris begins to wonder if it is not incompetence around chemicals but a memory problem the students have?

Suddenly Mr Boris remembers an infomercial he saw the night he came home from the Summertown Staff Christmas Party, that advertised a set of CDs on memory training. These CDs were available to purchase in 10 easy payments of $9.99 – a bargain when Mr Boris considers the price of the equipment and furniture he may be forced to replace! Mr Boris gets on the Internet and goes to Homeshop Ltd. and orders his copy. The CDs arrive just in time for the new school year.

The memory programme by famous cognitive psychologist Dr Drack Ular claims to improve the efficiency and accuracy of memory and all you have to do is complete a memory activity each week for the length of the school year. Mr Boris thinks this is worth trying and he administers a standardized memory test in the first week of class.

Mr Boris then diligently gives 39 Year 9 students Dr Ular’s  set memory tasks at the same time each Friday for the length of the school year. At the end of the year, Mr Boris then re-administers the memory test to see in there has indeed been an improvement. The memory test is an accepted measure of memory and is scored /100. A high score indicates good memory performance and a low score indicates poor memory performance.


Question 1

What statistical analysis would you use to analyse the data from this design, and why? (Approximately 50 words)




Question 2

Explain why each of the factors below can (or cannot) be ruled out as a threat to the internal validity of any conclusions Mr Boris and the experimenter may seek to draw.

For each answer,

  1. Define the term (using one or more references)
  2. State whether the effect can or cannot be ruled out
  3. Present an argument as to why (or why not) the effect can be ruled out.

You can use e-Topic notes, alongside any additional resources, to complete this question. See also the marking criteria for further details.


  1. a) History effects (Approximately 50 words)


  1. b) Maturation effects (Approximately 50 words)


  1. c) Mortality effects (Approximately 50 words)


  1. d) Regression to the mean (Approximately 50 words)


  1. e) Testing effects (Approximately 50 words)




Question 3

Use the data on the following page to conduct the appropriate analysis, then write the entire Results section for this experimental finding (No more than 200 words).

Use the same procedure you followed when writing the Results section in Part 1 and use the Hills (2011) text for your template.


ID Sex Age Before Memory Intervention After Memory Intervention
1 M 13 64 94
2 M 13 55 95
3 M 15 54 95
4 M 13 51 87
5 M 12 60 85
6 M 15 50 90
7 M 13 62 96
8 M 13 55 89
9 F 13 54 92
10 M 14 56 95
11 F 13 59 87
12 M 13 58 86
13 M 13 63 91
14 M 13 59 85
15 M 14 67 93
16 M 14 67 91
17 M 12 75 99
18 M 13 70 84
19 F 13 70 94
20 F 13 69 91
21 F 13 59 80
22 M 13 72 91
23 M 13 60 81
24 F 13 64 84
25 M 14 70 90
26 F 13 65 85
27 F 13 66 86
28 F 13 77 96
29 F 13 74 86
30 F 13 70 88
31 M 13 68 85
32 M 13 68 85
33 F 13 70 86
34 M 13 66 81
35 F 13 63 78
36 F 13 73 86
37 F 13 59 80
38 F 13 75 87
39 F 13 63 78


Writing Up Your Partial Research Report


In your professional lives, during the course of a research project you will often know the researchers, participants or confederates in your study. If such a situation arises, as a professional it is important that you proceed ethically. Some ways in which you can do this include:


  1. De-identifying all data. Never refer to anyone by name – this includes the names of Institutions (e.g., Schools or Clinics).
  2. Report group data, not individual scores. The group mean was.. The mean for males was.. etc.
  3. Always write using formal academic language, mostly in the third person and past tense.


For example, you may find yourself as part of a mental health team that decides to write a paper comparing the treatment regimes of a group of clients with phobias. At your clinic, Dr Smith is treating clients with phobias using a Cognitive Behavioural Intevention whilst Dr Brown is implementing a Meditation/Visualisation technique. Your clinic is located in Springmeadow, Sydney, and is called The Royal Phobia Treatment Centre. Over the course of the year, you as the Centre Director, get to know most of the clients by name.


In this example, any information that could identify the clinic, the practitioners, or most importantly the clients, would be removed or generalised. Therefore, when situating the study, you would refer to the clinic in general terms, for example, a phobia treatment clinic in Sydney, Australia. Likewise, the clinicians themselves would not be named, instead the treatment groups would be referred to collectively as the CBT Group and the MV Group (if necessary the practitioners may also be referred to as Clinician A and Clinician B). You would talk about the study in the third person and not identify yourself as the Director of the clinic or by name. Instead, if required you would state, “The aim of the current research..” or “It is predicted that…” etc. Not “Director Jones predicts that…”


In relation to the clients themselves, no names would be used and only general demographics provided (e.g., descriptive statistics on age and/or gender). A range of phobia test scores (including minimum and maximum scores) for each group may be necessary, but there should be no way of identifying which clients specifically obtained those minimum and maximum scores.


In our research example, though Summertown High is clearly a fictitious school and it has been fun (and often amusing) learning about the different predicaments of the staff and students, when it comes to conducting our assessment research, we must be both professional and ethical. Therefore as practice for the real-world, you will follow the same standards for our fictitious scenario, as you would if you were the member of any research project. This means following the three steps indicated above and you may use the clinic example provided in this document for guidance.


You may however take some artistic license and assume Summertown High is a Selective State High School located in Sydney, Australia.

  1. I don’t know how to enter the data for Part 1!


This is part of the assessable content so I cannot tell you how to do this, however the following steps will guide you in the right direction.


  1. Formulate your DIRECTIONAL hypothesis
  2. What is your IV and how many levels does it have?
  3. What is your DV?
  4. Based on your hypothesis (what you are trying to test and the number of groups), what type of test/analysis will you need to do?
  5. Go to that test’s Demo Data and see how the IV and DV have been entered and ask yourself “how can I make my data into a format that fits with that entry template?”.
  6. If all else fails, see Q6 below.


If you are still unsure, email me using your usual vUWS function with the answers to questions a) through to d) this will tell me how you are thinking about the research design and then I can guide you further.


Also, don’t forget the hint I gave after Week 4 classes.. “Now you will have done the analyses you need to complete Assessment 1..”



  1. Do we include SPSS output?


Yes, you include the SPSS output for your two analyses in two separate Appendices at the end of your assignment. Don’t simply dump the entire SPSS output, but include only the output you actually used to screen your data and run the analyses. If you “looked at it and used it in the writing of your assignment”, then include it.





  1. Do I need to include a Table or Graph?


Use the result section in the Hills (2011) text that corresponds with your chosen analysis. If Hills uses a Table, you use a Table too. Make sure you follow APA formatting protocols.



  1. Can I use headings?


Yes you can use a question/answer format. The only exception is in Part 1 where you present a partial research report and this should follow the standard APA formatting protocols for this.




Last paragraph of Introduction….










First paragraph of the discussion….


For more information on APA formatting protocols, please see your Writing For Psychology Guide from first year. If you do not have this book, the library has several good resources Additionally, the following links may be useful


  1. Do I screen a lot of variables for outliers and normality in Part 1?


You only screen the DV you are analysing as you did in the demo exercise for the particular test you have chosen. See also Hint (in red above)



  1. There is a column of data missing called Overall Risk Factor – do I have to calculate this?


Yes, and this is part of the assessment so I cannot tell you directly how to do this. If you are having difficulties, email me with the answers to Question 1 on the FAQ Sheet and I will then be able to guide you with this process.


  1. Why are there so many variables for Part 1?


There are several reasons for this that will become clear as you go along and this makes up part of the assessable content. I will give you a hint.. you may need some variable for sections and questions other than the specific analysis of your result section.



  1. Do I screen a lot of variables for outliers and normality for Part 3?


Again, follow the recommendation in Hills (2011) and your Demo Exercise for this analysis.



  1. I’m feeling stuck! How do I get started?


Start with Part 3 – this section of the assessment will get you on a roll J


  1. Is Part 1 complicated?


No, do not overthink the analysis or hypothesis for Part 1. You would not be given an analysis for this assessment that was complex or one you hadn’t had practice with (see also Hint in red above). Treat Part 1 like a “big” demo or assessment exercise and formulate your hypothesis based on Principal Foster’s* theorising as we have been doing in class. Once you have your hypothesis, you can work out your IV and DV as well as what analysis you will need. The hardest part is calculating the “Overall Risk Factor Score” and that’s not difficult J



* Don’t forget to write in the third person, past tense, and de-identify your data as per the Writing Up  guide in the assessment folder.



  1. Where do I find information on the methodological flaws?


The methodological flaws are written using a culmination of all your Experimental Design knowledge so far – after all, the unit is called Experimental Design and Analysis and we have tested your analysis skills, now it’s time to see your design skills.


In this section you need to think about the result of your Part 1 analysis and what (other than your IV) may have contributed to it. We expect our DV to be significant or not as a result of the IV…. but what if there is something else that made the DV go up or down (be significant or not)? Did we design our experiment to control for these other factors (extraneous variables)? Or are there extraneous variables that we can’t control for no matter how hard we try that could have affected our DV?


For example, I hypothesise that Males have a significantly greater mean height (in cms) than females. I base this on theory and statistics from around the world, so I am feeling confident. Off I go to collect my data and I collect a sample of 30 females from The Bankstown Boomers Women’s Basketball team and a sample of 30 males from the AJC (Australian Jockey Club).  I run my t-test and find that women are significantly TALLER than males. This goes against my experimental hypothesis, so I have to accept the null. If I were to write up the methodological flaws in this study I would examine what, other than my IV of gender (being biologically male or female) could have resulted in my DV (height) being significantly higher for females than males. Was my study badly flawed or will I become famous by rewriting the world’s findings on gender and height?????


This of course is a very simplistic example, but it gives you an understanding of what methodological flaws do and how to think about identifying them. What was the outcome of your analysis and what else could have been responsible for this (other than your IV)?


  1. How to calculate Overall Risk Factor..


I can’t say too much, as this is part of your assessment, but I can give you the following information for guidance – You need to calculate the overall risk factor score that is comprised of several risk factors identified by the research (Perceived Quality, Caregiver Involvement, Overall Grade, Attendance). These scores are also out of 100, so simply adding them up would give you a risk score out of /400, but you are required to provide a risk factor score /100, so somehow the score out of 400 needs to be out of 100. There are a couple of ways to achieve this score /100.


This new variable “Overall Risk Factor” is the only variable you need to screen or analyse.


Of course, if you still wish to email me with the answers of a) through d) from FAQ 1 for feedback, you are welcome to.


Details on Measures:

Perceived Quality of School Scale

  • This scale measures the student’s perception concerning the school’s quality of education and the teachers’ work, the number of vocational and practical classes provided, the encouragement provided by the school, and the importance of what is taught at the school.
  • This scale is scored out of 100 and a high score indicates high levels of perceived quality and a low score indicates low levels of perceived quality.
  • Research shows low perceived quality of one’s school is linked to higher levels of dropping out.

Caregiver Engagement Inventory

  • This scale measures the involvement of the family and other significant adults in the student’s school life. The measure examines factors such as the extent to which this adult network expects good grades, appropriate behaviour, and high levels of school attendance.
  • Additionally the scale measures the adults’ level of involvement with the school and the encouragement provided to the student.
  • This scale is scored out of 100 and a high score indicates high levels of involvement and a low score indicates low levels of involvement.
  • Research shows low levels of family/caregiver involvement are related to higher levels of dropping out.



Further Reading:


Soares, T.M., da Silva Fernandes, N., Nóbrega, M., & Nicolella, A.C. (2015). Factors associated with dropout rates in public secondary education in Minas Gerais Educ. Pesqui., 41(3).

Lamm, A., Harder, A., Lamm, D., Rose, H., & Rask, G. (2005). Risk Factors Affecting High School Drop Out Rates and 4-H Teen Program Planning. Journal of Extension, 43(4), 201-205.

Part 1

Title: Analysis of the Risk Factors with pilot study


The focus has been on the local area school directorate which concerns about the attrition rates for the high schools. For this, the risks factors are related to the drop out patterns to conduct the pilot study. The work has been done to focus on the lower caregiver engagement with the school, grades and the absenteeism. The overall risk factors are about the chosen school of Winterfield Grammar to highlight about the study by LASD. (Subramani et al., 2016). The research measures also includes the literature with the association with increased dropout rates. The success is for the performing arts where the myriad is of practical and vocational classes.

Material & design

The material and the designing is for the involvement of different activities which are related to attend the high school. There is a need to analyse the tests with the calculation of overall risks factor score. The procedures include the performance of arts in the high school along with the directional hypothesis. The examination is for the de-identification of the data where no one is referred to anyone by name. It also includes the different schools or the clinics. There are no individual scores which are assigned but a mean value is calculated for the group through the SPSS data. (Coakes et al., 2009). The cognitive behavioural intervention is through the implementation of visualisation technique where the clinic is set to handle the clients with the removal or the generalisation process. The MV group is based on the directory where the research could be set through the descriptive statistics which also includes the minimum and the maximum scores to group and could be necessary to identify the client’s scores. The research is about the learning for the different predicaments of staff and students when it mainly comes to conducting the research of assessment. The phobia of the treatment clinic in Sydney is depending upon the identification of clients, clinic. Through the SPSS data, it is easy to find the analysis and the skills that are mainly to design the experiments and control the other extraneous variables. (Norusis, 2008). It is also for the controlling of the theory and statistics from the different standards. The standards for the research and data management through descriptive and correlation which works on simplified repetitive tasks and handling the data complexity. The standards are based on scripting facilities to work on the different menu structure.


The analysis has been done using SPSS. The data has been entered in the SPSS workspace, and the tools has been used for the analysis. To analyse the part, we have first entered the provided data in the tables of SPSS, and then the data was discriminated using ANOVA. The analysis functions that are prebuilt in SPSS has been used. The plots that were used in SPSS are also produced from the graph sections of SPSS. The data has been directly considered for testing without any training set, as the criteria for the same has already been provided. The confidence percentage has been set to 95% confidence interval of the difference. The lower and upper bounds of the data have been calculated to reach the results. The data tables and plots for all the analysis has been included in the SPSS file attached separately.




The discussion is about the LASD measures where the performance is based on pro-activeness in the school. It is also based on allocating higher standards and affinity which is to meet the requirements as well as the other interests of the Winterfield Grammar. The overall risk factor is evaluated through the data processing where the data holds the case-by-case analysis in the file. (Pepin et al., 2000). Here, there are variable structures and processing based on the representation of variable and other variety of characteristics. With the data entry, the format is for the personal interviewing as well as recognition of datasets read into SPSS statistics.



Part 2

Design Flaws 4 issues

The issues are related to the t tests which is for the sampling distribution. For the two group structure, there is a need to find out the difference in between the random numbers which is set between the independent and the repeated groups. (Xiaosheng et al., 2010). For this, the two independent samples are generally selected in a random manner and then is compared to the other controlling factors. The samples are related to the ratio level data with the normal distribution and homogeneity of variance. The variance is set as per the standard deviation which is then to measure the demonstrations for the non-parametric tests. The issue is also with the dependent variable which need homogeneity of variances. The SPSS use the Levene’s test to work on the enhanced performance while interpreting the data. The reduction is in the validity of results along with categorising the independent variables for the different groups. The standards are met to include the employment status, where the observations are also based on enhanced independent t-tests.

There are issues with the type 1 error, power of the test, internal and external validities are also found to be at stake. Hence, it is important to test the normality with the skewness and kurtosis where the scores are significant for the relational database patterns. The statistics also works on the different versions of SPSS data where the prediction of the numerical outcomes could be easily done through the linear regression. Hence, the identification is accessible through the menu structure in an effective manner.

Part 3

Design Effects

Part 3 Scenario

Question 1

The statistical analysis to be used to analyse the data from this design would be the percentage analysis of the results. The analysis will consist of percentage of the correct answers after the test is conducted. This will give an idea on the effectiveness of the test.


Question 2

  1. History Effects

History effect is the effect of past experience of the subject under analysis in the statistical analysis. In this case, the effect cannot be rules out, as the person with already low memory retain capability will of course retain less than other even after the memory curse.

  1. Maturation Effect

In this effect, the subject under analysis will have reached optimum level and may not be able to accept any more improvement. The case here cannot be ruled out. This is because, there is a limit to how much a person can remember and retain under normal circumstances. Exceeding it is difficult task.

  1. Mortality Effect

The end of a scenario is considered mortality effect. It can be ruled out in this case as there is no end to the retaining of the memory of the user of the course. The person can apply and deploy the memory retention plan in every situation and can always use it even outside the test scenarios.

  1. Regression to the mean

Regression to the mean is the consideration of the regression of the data from the mean or average value. Here, in the analysis, it cannot be ruled out as the deviation can be considered to analyse if the plan and course for memory retention should be followed on students. If there is not much effect from the mean, then the course can be discarded.

  1. Testing effects

The effect of being under the test scenario is the testing effect. The effect cannot be ruled out as many subjects under test may behave differently as compared to in normal situation. This would mean that students could remember more or less in the normal situation, which might be different from the test results of analysis.

 Question 3


The data has been analysed using SPSS statistical analysis tools. The data has been entered in the SPSS environment and the results has been drawn based on tables and regression curves. After analysis, it can be said that the test shows that memory retention plans have effects on students. The effect is more on female students than on male students. Thus, the plan could be used for retention of memory.


Subramani, T., & Tamizhanban, S. (2016). Supply Chain Management In Construction Site By Using SPSS Software. benefits5(3).

Coakes, S. J., & Steed, L. (2009). SPSS: Analysis without anguish using SPSS version 14.0 for Windows. John Wiley & Sons, Inc..

Norusis, M. (2008). SPSS 16.0 statistical procedures companion. Prentice Hall Press.

Pepin, M., Schwarze, U., Superti-Furga, A., & Byers, P. H. (2000). Clinical and genetic features of Ehlers–Danlos syndrome type IV, the vascular type. New England Journal of Medicine342(10), 673-680.

Norušis, M. J. (1990). SPSS base system user’s guide. Prentice Hall.

Xiaosheng, L., & Zhenzhen, C. (2010). Correctly Using SPSS Software for Principal Components Analysis [J]. Statistical Research8, 105-108.