Statistic Questions using PSPP

User Generated

Wbfcrughegyr

Mathematics

Singapore University of Social Sciences

Description

I will attach the whole assignment consists of total 3 questions. I have input the pre-task data required which is the data from 20 questionnaire into the PSPP. I will also attach the screenshot and the data itself for reference. Do take note the number of pages does not matter, this is a question and answer based type question. My deadline is tomorrow (26/9/2018) before 6pm (GMT+8). Would appreciate if anyone could help as due to time constraint im not able to do this assignment. Thank you!

The data file.sav seems to be unable to upload. Please let me know if I can send to you through other means. Thank you!

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PSY392 Methods of Data Analysis: Exploring Behavioural Sciences Tutor-Marked Assignment 01 July 2018 Presentation PSY392 Tutor-Marked Assignment 01 July 2018 Semester PSY392 TMA01 This tutor‐marked assignment (TMA) is worth 20% of the final mark for PSY392 Methods of Data Analysis: Exploring Behavioural Sciences. There is no word limit for this TMA. Please upload this assignment to Turnitin by Wednesday, 26 September 2018, 11:55pm. Multiple submissions are allowed before this cut-off time. TMA format [New! Please take note] • Download and complete the new TMA Cover Page (screenshot below) from Canvas L01 > Modules > Assessments. • Acknowledge that you have read the self-declaration on academic integrity and submit it with your TMA. There will be a penalty of 5 marks deduction if the TMA cover page is incomplete, inaccurate or missing from the final submission of your TMA via Turnitin. No appeals concerning the Cover Page will be entertained. • Use Times New Roman 12 point, double line spacing throughout. SINGAPORE UNIVERSITY OF SOCIAL SCIENCES (SUSS) Page 2 of 8 PSY392 Tutor-Marked Assignment 01 July 2018 Semester TMA submission – read these instructions carefully • Backup your TMA at all times. • Submit early and check the originality report for possible revision and resubmission. • Turnitin reports are generated immediately the first time but subsequent reports may take up to a day to generate. • Multiple submissions (overwriting earlier submissions) are allowed before the deadline, but no further submissions during the grace period or thereafter. • Upload TMA in Word document file only (not in PDF), and strictly follow the naming convention specified for TMA files (Non-compliance to these standards might lead to an admin fee and/or the TMA not be being marked). • Upload correct TMA file to the correct folder of the correct course. Admin fee applies to appeals to transfer files to correct folder. • 12-hour grace period after the deadline is for resolving technical problems encountered with submissions before the deadline. • In case of problems: Email Canvas Support LSsupport@suss.edu.sg immediately (with relevant screenshots and your TMA attached) and follow up with Canvas Support before the grace period is over. • If there was no submission before the deadline, one late submission is allowed after the deadline for up to 1 week, after which no more late submissions will be allowed. • Automatic marks deduction applies after the 12-hour grace period (refer to the marks deduction scheme in the Student Handbook). With this automatic deduction, there will be no need to request for extensions from your tutor because your tutor does not have the mandate to over-ride the Canvas system settings. • Retain the Turnitin digital receipt as evidence of a successful submission. Appeals submitted without the Turnitin digital receipt will not be entertained. • View your submission immediately to ensure that the entire document has been uploaded completely and successfully. SINGAPORE UNIVERSITY OF SOCIAL SCIENCES (SUSS) Page 3 of 8 PSY392 Tutor-Marked Assignment 01 July 2018 Semester Word Limit Please observe the word limit as writing succinctly is an important skill to acquire in academic writing. All text (including in-text citations) is included in the word count except the reference list, tables, figures, and appendices. Note that anything written beyond 10% of the word limit will not be marked. Plagiarism and Collusion The assignment is to be completed on your own. You may discuss the TMA with your coursemates, however, the assignment must be written up independently. Do not share your notes, draft or final TMA with anyone before the marked TMAs are returned to you. Avoid plagiarism by giving yourself sufficient time to research and understand the material so that you can write up your assignment in your own words. Quotations should be used sparingly. Simply citing the source of ‘copied’ chunks of text does not excuse it from plagiarism. Do ensure that any paraphrasing is done appropriately (even if you use text from your own work that you have submitted as part of another assignment of the same or another course). The University takes a very serious view of plagiarism (passing off someone else’s ideas as your own, or recycling of contents from your own earlier marked TMA from the same course or another course) and collusion (submitting an assignment which is the same or very similar to another student’s). Both are very serious academic offences. Please refer to the Student Handbook on the penalties of plagiarism or collusion. You are strongly advised to submit your TMA early, check the plagiarism report yourself, and if needed revise and resubmit your TMA before the submission deadline. SINGAPORE UNIVERSITY OF SOCIAL SCIENCES (SUSS) Page 4 of 8 PSY392 Tutor-Marked Assignment 01 July 2018 Semester Marks allocation at a glance Deduct 5 marks if the new TMA Cover Marks Page is incomplete, inaccurate or missing. Pre-TMA Task 10 Question 1 a 5 b 15 c 10 a 15 Question 2 b 15 a 5 Question 3 b 10 c 15 100 Total Note: All marks will be awarded only with the TMA submission via Turnitin. Pre-TMA Task (10 marks) Download the folder “completed questionnaires.zip” from Canvas L01> Modules>Assessments, enter the data from the 20 questionnaires into a PSPP data file, properly name each variable that you have in the data file, and define the necessary value labels. Capture screenshots of the Data View and Variable View of your data file and paste them on your assignment. Question 1 (30 marks) a) Examine the following variables from the data file and identify the appropriate scale of measurement for each: i) ii) iii) iv) v) Participant ID Gender Number of Older Brother(s) Number of Younger Sister(s) IQ Score (5 marks) b) Using PSPP/SPSS, calculate and examine the descriptive statistics for the following variables separately for male and female participants: i) Number of Older Brother(s) ii) Number of Younger Brother(s) iii) Number of Older Sister(s) iv) Number of Younger Sister(s) v) IQ Score Present the results in a table following the APA format. Note: Please cut and paste your PSPP/SPSS output into your answer to demonstrate that you have used PSPP/SPSS. (15 marks) SINGAPORE UNIVERSITY OF SOCIAL SCIENCES (SUSS) Page 5 of 8 PSY392 Tutor-Marked Assignment 01 July 2018 Semester c) Construct an appropriate graph following the APA format to display mean IQ Score by Gender. You may use PSPP/SPSS or Excel to help you construct the graph. Interpret the difference in IQ Score between male and female participants. (10 marks) Question 2 (30 marks) a) The population mean and standard deviation of the number of siblings are 1.82 and 0.78, respectively. Formulate the necessary hypotheses, apply the appropriate test, and interpret if the mean number of sibling in our sample is different from the population. Report your results in APA format. Note: Please show the necessary calculations for the test that you conducted. (15 marks) b) Five more new participants were recruited into the study. After including their data, the proportions of males and females in the sample are 44% and 56%, respectively. The mean IQ Score is now 108.8. Apply the necessary formulas to: i) Determine the number of new male and female participants. (4 marks) ii) Calculate the mean IQ Score of the five new participants. (6 marks) iii) Calculate the standard deviation of the IQ Score for the new sample if the ΣX2 of the new sample is 300505 and the (ΣX)2 is 7403814. Note: Please show the necessary calculations in your answers. (5 marks) Question 3 (30 marks) The population mean and standard deviation of IQ Score are 100 and 15, respectively. a) If a person has a z-score of 0.5, apply the necessary formula to: i) Calculate his/her raw IQ Score (2 marks) ii) Determine his/her relative position for IQ Score in the population Note: Please show the necessary calculations in your answers. (3 marks) SINGAPORE UNIVERSITY OF SOCIAL SCIENCES (SUSS) Page 6 of 8 PSY392 Tutor-Marked Assignment 01 July 2018 Semester b) If a sample of 36 people is randomly drawn from this population, apply the necessary formula to: i) Calculate the standard error of the mean for the mean IQ Score of this sample. (2 marks) ii) Analyse and determine the probability that the mean of IQ Score, from a random sample with N = 36, is > 102.5 Note: Please show the necessary calculations in your answers. You may want to use the concepts of central limit theorem, sampling distribution, and sampling error to help you answer this question. (8 marks) c) If we want to the probability of the sample mean > 102.5 to be 1%, how many people should we randomly sample from the population? Apply the necessary formula to obtain the answer. Note: Please show the necessary calculations in your answers. You may want to use the concepts of central limit theorem, sampling distribution, and sampling error to help you answer this question. Round off your final answer to the nearest whole number. (15 marks) SINGAPORE UNIVERSITY OF SOCIAL SCIENCES (SUSS) Page 7 of 8 PSY392 Tutor-Marked Assignment 01 July 2018 Semester Generic Band Descriptors for Students Excellent answer • shows a clear and thorough understanding of the topic concerned by covering relevant points accurately and comprehensively in a well-structured, focused and cohesive manner • provides excellent illustrations/examples/supporting evidence • shows very strong evidence of critical thinking/analysis and in-depth understanding • goes beyond expectation and shows original thinking Good to Very Good answer • shows a good to very good understanding of the topic concerned by covering relevant points accurately in a well-structured, focused and cohesive manner • provides good illustrations/examples/supporting evidence • shows good evidence of critical thinking/analysis and in-depth understanding Fair answer • shows a fair understanding of the topic concerned by covering relevant points adequately, but may not always be well structured, focused and cohesive • provides adequate illustrations or examples, however, they may not always be appropriate • shows little evidence of critical thinking/analysis and lacks in-depth understanding Weak answer • shows only rudimentary understanding of the topic concerned and only manages to cover a relevant point or two adequately, but is not well structured, focused and cohesive • attempts to provide illustrations or examples, however, they are generally inappropriate or irrelevant • shows no evidence of critical thinking • may contain inaccuracies and omissions Poor answer (borderline pass) • does not show adequate understanding of the topic concerned and may not sufficiently cover any of the relevant points • does not provide illustrations or examples • tends to be descriptive and may be off-point • contains errors and misconceptions Fail (less than 40%) • shows very little understanding of the topic concerned and does not cover any of the relevant points • fails to provide illustrations or examples • attempts to describe but is off-point • contains serious errors and misconceptions Bad Fail (less than 15%) • shows no understanding of the question • some marks may be awarded if there is evidence that some effort was made to make sense of the question --- End of TMA --SINGAPORE UNIVERSITY OF SOCIAL SCIENCES (SUSS) Page 8 of 8 Case ParticipantID Gender NumberofolderBrothers NumberofyoungerBrothers Numberofolder Sisters Numberofyounger sisters IQScore 1 14966 2 0 0 0 1 128 2 21758 2 1 1 0 0 87 3 32652 1 0 1 0 0 104 4 37124 1 0 0 0 0 90 5 38687 2 0 1 1 0 120 6 41741 2 2 1 0 1 95 7 43939 1 0 0 0 1 126 8 49953 2 0 1 0 0 103 9 53823 2 0 0 2 1 101 10 55102 1 0 1 1 0 88 11 55909 1 0 1 0 1 127 12 67596 1 0 0 2 0 96 13 70690 2 1 0 0 0 118 14 73358 1 1 0 0 2 115 15 80375 1 2 0 0 0 118 16 81020 2 0 1 0 1 100 17 81249 1 1 2 0 0 110 18 87684 1 0 1 0 2 122 19 93723 2 0 2 0 1 131 20 93798 2 0 0 0 0 116 21 *Birth Order and Intelligence Study.sav [DataSet1] — PSPPIRE Data Editor File Edit View Data Transform Analyse Graphs Utilities Windows Help X> Value Labels Missing Values Column Align Measure Role Variabll Name Type Width Decimal Label 1 ParticipantID Numeric ... 8 Participant ID 0 None ... None ... 12 Right = Nominal Input 2 Gender Numeric ... 18 0 Gender {1, Female}... ... None ... 8 Right = Nominal Input 3 Numberofolder Numeric ... 18 0 Number of Older Brother None ... None ... 20 Input Right Scale Right = Scale cf | | | | | | 4 Numberofyoun Numeric 8 0 Number of Younger Broti None None ... |24 Input 5 Numberofolder Numeric ... 18 lo Number of Older Sisters None ... None ... 19 Right = Scale Input 6 Numberofyoun Numeric ... 8 8 0 Number of Younger siste None ... None BE 22 Right Scale Input 7 IQScore Numeric ... 8 0 IO Score None None M ... | 8 Right Ordinal ul Input 8 .
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