Statistics Data analysis

Anonymous
timer Asked: Jan 4th, 2018
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Question description

Please see the attached files for details. I have attached 3 files. One file has the assignment details, second is the sample report and last file is format for the report.

I will give the data set file after allocating you the question as I can not upload it here (it comes back as invalid file).

You need SPSS software for this assignment.

01/01/2018 Assignment 2: Analysis of data Teaching period 3, 2017 STA10003: Founda ons of Sta s cs Assignment 2: Analysis of data Word limit: Maximum of 5 pages (1 page for each analysis) Weighting: 20% Due date: 5pm AEDT Monday 8 January 2018 (Week 8) After you have read this information, head over to the Assignment 2 Q&A discussion board to ask any questions and see what your peers are saying about this assignment. Assignment overview For this assignment you will utilise SPSS to conduct data analysis of mental health service data in five specified areas, and then write a brief report on each area. Assignment details Scenario You are a new graduate at a health sciences research institute, and the lead researcher has given you a dataset which requires analyses and a written report on which you will be graded according to the rubric in the section below. The data set is based on the Australian Health Survey from the Australian Bureau of Statistics (ABS) collected over the period from 2011 to 2012. The original data file contained over 17,000 observations, and a representative subset of the original data containing 8,525 observations (STA10003­data­2016.sav) is located in the additional resources section below. Data prepara on Before attempting the Assignment questions, you must use SPSS to draw a random sample of 2000 (from the 8,525 cases). You will conduct your analysis on your sample of 2,000 observations. Instructions on how to generate your random sample are contained in the additional resources section. Note, however, that some variables contain missing values, so each of your analyses might not contain the entire 2,000 cases. https://swinburneonline.instructure.com/courses/101/assignments/507 1/9 01/01/2018 Assignment 2: Analysis of data Data analysis For your assignment, you are required to complete the following five questions by producing the appropriate analyses and writing the relevant report for each question. The reports should follow the format of the model reports provided in the additional resources section. Note: For each question you should include the relevant output (e.g. tables, confidence interval calculations and graphs) with your report. You are required to produce the following five sets of analyses. Each analysis should be accompanied by a brief report (each report should be no more than one page). Page Description Instructions 1 Produce the relevant graph and table to summarise the ‘SA_Health’ variable and write The variable ‘SA_Health’ indicates the self­assessed a paragraph explaining the key features of the data observed health status reported by participants. in the output in the style presented in the course materials. 2 Produce the relevant graph and tables to summarise the ‘FRUIT’ variable and write a The variable ‘FRUIT’ measures the number of serves paragraph explaining the key of fruit eaten per day by respondents. features of the data observed in the output in the style presented in the course materials. 3 The lead researcher has information relating to exercise levels from the 2011 National Health Survey in the United Kingdom, which shows that 32% of participants have an exercise level considered to be sedentary. The researcher thinks that Australians might be more active due to better weather conditions, and suggests that the percentage of sedentary people in Australia is less than 32%. The variable ‘Ex_Level’ indicates the level of exercise of participants. Conduct a Binomial test using the ‘Ex_Level’ variable to test the researchers claim. Produce the relevant output and write a Binomial test report based on your output in the style presented in the course materials. 4 The variable ‘BMI’ indicates the Body Mass Index of the respondent at the time the survey was undertaken. Information from the 2011 National Health Survey indicated that in the UK the BMI score was 27. Australian Health reports have continually stressed that Australian obesity rates are getting higher, so the researcher expects that the average BMI score for Australians is higher than 27. Conduct a One­sample t­test using the ‘BMI’ variable to test this claim. Produce the relevant output and write a One­sample t­test report based on your output in the style presented in the course materials. https://swinburneonline.instructure.com/courses/101/assignments/507 2/9 01/01/2018 Assignment 2: Analysis of data Page 5 Description As many women report being on a diet, the researcher thought that females eat more fruit and vegetables than do males. Instructions Conduct an Independent samples t­test using the ‘FRUIT_VEG_COMBINED’ and ‘GENDER’ variables to test this claim. Produce the relevant output and write an Independent samples t­test report based on your output in the style presented in the course materials. Addi onal resources The data set is from the Australian Health Survey from the Australian Bureau of Statistics (ABS) 2011­2012, STA10003­data­2016 (SAV 332KB) . Assignment 2 template (DOC 27 KB) . This document is not compulsory, you do not have to use it. It is simply a template for how to format the page layout of your assessment. Whilst we do strongly recommend you adopt this format and use the template, you will not lose marks for not doing so. Please rename the document to match your surname and student number. Model reports (DOCX 56KB) relevant to Assignment 2. Instructions for generating random sample (PDF 681KB) . Modifying your assignment data file to produce the binomial test. The videos below were produced for a previous dataset but the processes outlined remain the same. Please note the total number of participants is different in this dataset. You will be selecting a random sample from the total number in your current dataset. The PDF instructions above also outline these processes. Ass-2-Generating_Random_Samples_of_2000_cases from Swinburne Online https://swinburneonline.instructure.com/courses/101/assignments/507 3/9 01/01/2018 Assignment 2: Analysis of data 04:25 Video 1: Generating your random sample of 2000 cases (2016) created by Swinburne Online Ass-2Modifying_your_2000_cases_data_for_Binomial_Test from Swinburne Online 03:18 Video 2: Modifying your 2000 cases data for the binomial test (2016) created by Swinburne Online Checklist Correct procedure performed. Correct variable used to produce output. Graphs appropriately edited and labelled (e.g. edited variable names; 'Figure 1. The distribution of …'). Correct test values used. All figures quoted in report correct according to your own output. Including 95% confidence interval interpretations where appropriate. Significance interpreted correctly (i.e. check that you are not saying the finding is significant when it is not or vice versa). Correctly referring to the sample or population where appropriate. Proof reading of reports for errors. Submission details overview This assignment will be submitted via Turnitin. You will find the relevant submission point below. https://swinburneonline.instructure.com/courses/101/assignments/507 4/9 01/01/2018 Assignment 2: Analysis of data Please allow a 24­hour turnaround for an originality report to be generated. See the Turnitin originality report (https://portal.swinburneonline.edu.au/study­resources/turnitin­originality­ report­0) area of Study Resources for several guides to assist with the submission process. Assignment support Don't forget that in addition to your eLAs who provide discipline­specific content advice, you can access the 24/7 draft writing service from Studiosity. If you need assistance with academic feedback on a draft of your assignment task see Assignment support: Studiosity. Assignment criteria 1. 2. 3. 4. 5. Summary of categorical variable. Summary of metric variable. Binomial test. One­sample t­test. Independent­samples t­test. Your work will be assessed using the following marking guide: Criteria No Pass Pass 50­59% Credit 60­69% Distinction 70­79% High Distinction 80­100% Summary of categorical variable (20%) Did not meet criterion. Appropriate graphs and tables for categorical data. Reasonable attempt to summarise what is seen the in data. Appropriate graphs and tables for categorical data. Graphs and tables suitably edited for presentation (titles, rounding, etc.). Written summary covers all relevant features of output. Appropriate graphs and tables for categorical data. Graphs and tables suitably edited for presentation (titles, rounding, etc.). Written summary covers all relevant features of output and is clearly and concisely written. All of the criteria for Distinction with no errors and outstanding written communication. https://swinburneonline.instructure.com/courses/101/assignments/507 5/9 01/01/2018 Criteria Summary of metric variable Assignment 2: Analysis of data No Pass Pass 50­59% Credit 60­69% Distinction 70­79% High Distinction 80­100% Did not meet criterion. Appropriate graphs and tables for metric data. Reasonable attempt to summarise what is seen in data. Appropriate graphs and tables for metric data. Graphs and tables suitably edited for presentation (titles, rounding, etc.). Written summary covers all relevant features of output. Appropriate graphs and tables for metric data. Graphs and tables suitably edited for presentation (titles, rounding, etc.). Written summary covers all relevant features of output and is clearly and concisely written. All of the criteria for Distinction with no errors and outstanding written communication. Did not meet criterion. Correct output. Report presented following form at used in course materials and textbook. No major errors in report. More than 1 or 2 minor errors. Correct output. Report presented following form at used in course materials and textbook. Only 1­2 minor errors in report. Correct output. Report Presented following form at used in course materials and textbook. All of the criteria for Distinction and report is flawless. (20%) Binomial test (20%) https://swinburneonline.instructure.com/courses/101/assignments/507 6/9 01/01/2018 Assignment 2: Analysis of data Criteria No Pass Pass 50­59% Credit 60­69% Distinction 70­79% High Distinction 80­100% One­sample t­ test (20%) Did not meet criterion. Correct output. Report presented following form at used in course materials and textbook. No major errors in report. More than 1 or 2 minor errors. Correct output. Report presented following form at used in course materials and textbook. Only 1­2 minor errors in report. Correct output. Report presented following form at used in course materials and textbook. All of the criteria for Distinction and report is flawless. Independent­ samples t­test (20%) Did not meet criterion. Correct output. Report presented following form at used in course materials and textbook. No major errors in report. More than 1 or 2 minor errors. Correct output. Report presented following form at used in course materials and textbook. Only 1­2 minor errors in report. Correct output. Report presented following form at used in course materials and textbook. All of the criteria for Distinction and report is flawless. References The data is made available by: Australian Bureau of Statistics. (2012). 4364.0.55.001 ­ Australian Health Survey: First Results, 2011­12. Retrieved from http://www.abs.gov.au/AUSSTATS/abs@.nsf/Lookup/4364.0.55.001Main+Features12011­12? OpenDocument Assessment declaration and statement of authorship By submitting my assessments below I declare that: https://swinburneonline.instructure.com/courses/101/assignments/507 7/9 01/01/2018 Assignment 2: Analysis of data This is an original piece of work and no part has been completed by any other person than signed below. I have read and understood the guidelines on How to avoid plagiarism (https://portal.swinburneonline.edu.au/study­resources/how­avoid­plagiarism­0) and no part of this work has been copied or paraphrased from any other source except where this has been clearly acknowledged in the body of the assignment and included in the reference list. I have retained a copy of this assessment in the event of it becoming lost or damaged. I agree and acknowledge that: I have read and understood the Swinburne Assessment Declaration. I accept that use of my Swinburne account to electronically submit this assessment constitutes my agreement to the Swinburne Assessment Declaration. If I do not agree to the Swinburne Assessment Declaration in this context, the assessment outcome may not be valid for assessment purposes and may not be included in my aggregate score for this unit. Further information relating to the penalties for plagiarism, which range from a formal caution to expulsion from the University, is contained in the Student Academic Misconduct Regulations 2012 and at the Assessment declaration (http://www.swinburne.edu.au/current­students/manage­ course/exams­results­assessment/submit­work/assessment­declaration/) page. https://swinburneonline.instructure.com/courses/101/assignments/507 8/9 01/01/2018 https://swinburneonline.instructure.com/courses/101/assignments/507 Assignment 2: Analysis of data 9/9
Running head: ASSESSMENT 2 - ANALYSIS OF DATA Assessment 2 – Analysis of Data Name: Rhys Luckey Student ID: 12345678 Swinburne Online If you are using this template to start your assignment, please make sure you include your own name and student number above. Additionally, the file name should be renamed to include your surname and ID number. Once you’ve done this, remove this text. 1 ASSESSMENT 2 - ANALYSIS OF DATA Assessment 2 – Analysis of data Question 1 – Summary of a categorical variable Answer would go here. Question 1 – Summary of a categorical variable – SPSS Output Output would go here. 2 ASSESSMENT 2 - ANALYSIS OF DATA Question 2 – Summary of a metric variable Answer would go here. Question 2 – Summary of a metric variable – SPSS Output Output would go here. 3 ASSESSMENT 2 - ANALYSIS OF DATA Question 3 – Binomial Test Answer would go here. Question 3 – Binomial Test – SPSS Output Output would go here. 4 ASSESSMENT 2 - ANALYSIS OF DATA Question 4 – One Sample t-test Answer would go here. Question 4 – One Sample t-test – SPSS Output Output would go here. 5 ASSESSMENT 2 - ANALYSIS OF DATA Question 5 – Independent Samples t-test Answer would go here. Question 5 – Independent Samples – SPSS Output Output would go here. 6
Model Reports Relevant to the Assignment In this document you’ll find all of the model reports from the text which are relevant to the Assignment. Note that we’ve provided lots of model reports and they cover all possibilities. So, for example, in the one sample t-test you’ll find three model reports: for a significant t-test where the results supported the hypothesis; one report where the t-test was significant but the direction of the difference was contrary to expectations; and one report where the t-test was not significant. If you compare the three different one-sample t-test reports on the age of tourists in Katatonia you’ll see that they all have the same basis, with just minor changes for the three different outcomes Description of the distribution of a metric variable The distribution of house prices in a sample of 542 South Australian houses is displayed in Figure 1. The distribution is positively skewed with 50% of houses priced at $430,000 or less. Typically house prices were between $390,000 and $550,000 with half of the house prices falling within this range. Two houses had exceptionally high prices of $1,030,000 and $1,050,000. Figure 1 Distribution of house prices. The distribution of time taken to travel to work in a sample of 250 Australian workers is displayed in Figure 1. The distribution is approximately symmetric and the average travel time was 20 minutes (s = 5). Typically travel times were between 17 and 24 minutes with half of the travel times falling within this range. 25 Frequency 20 15 10 5 0 5 10 15 20 25 30 35 Time to travel to work (Minutes) Figure 1: Distribution of travel times to work Description of the distribution of categorical variable The distribution of main use of mobile phone for a sample of 98 Expencitel customers is displayed in Figure 1. The most common primary use was to send SMS messages (53%), but making phone calls was also a common response (43%). Very few people said that the primary use for their phone was either taking photographs or listening to mp3 files. Figure 1: Primary use of mobile phone 1 Foundations of Statistics_Model_Reports_Assignments One Sample t-test A study was conducted to investigate whether the age of tourists in Katatonia has increased since 1995. In a random sample of 250 tourists in Katatonia, the average age was 47.77 years (s = 15.41 years). This is higher than the average age of 45 years recorded in 1995, and one-sample t-test shows that this difference in mean age is significant, t(249) = 2.84, p = .005. The 95% confidence interval indicates that since 1995 the average age of tourists has increased between 0.85 and 4.69 years. As expected, the age of tourists in Katatonia has increased since 1995. A study was conducted to investigate whether the age of tourists in Katatonia has increased since 1995. In a random sample of 250 tourists in Katatonia, the average age was 41.43 years (s = 15.93 years). This is lower than the average age of 45 years recorded in 1995, and a one-sample t-test shows that this difference in mean age is significant, t(249) = 3.55, p < .001. The 95% confidence interval indicates that since 1995 the average age of tourists has decreased by between 1.59 and 5.56 years. Contrary to expectations, the age of tourists in Katatonia has decreased since 1995. A study was conducted to investigate whether the age of tourists in Katatonia has increased since 1995. In a random sample of 250 tourists in Katatonia, the average age was 44.84 years (s = 9.96 years). While this is lower than the average age of 45 years recorded in 1995, a one-sample t-test shows that this difference in mean age is not significant, t(249) = 0.25, p = .805. The 95% confidence interval indicates that the average age of tourists is between 1.40 years less and 1.08 years more than in 1995. There is insufficient evidence to conclude that the age of tourists in Katatonia has changed since 1995. Binomial test A study was conducted to explore whether the percentage of Australians using a computer at home has increased since the census in 2001. In a random sample of 100 adult Australians, 54% had used a computer at home in the previous week. This is higher than the percentage of Australians who reported using a computer at home in the 2001 census (42%), and a Binomial test shows that the difference is significant, n = 100, p = .010. The 95% confidence interval indicates that between 44% and 64% of adult Australians currently use a computer at home. As expected, the percentage of Australians using a computer at home has increased since 2001. A study was conducted to explore whether Kayden Real Estate rent more than 35% of their rental properties to families. In a random sample of 70 rental properties, only 24% were rented to families. This is less than the target set by the government authority (35%), and a Binomial test shows that the difference is significant, n = 70, p = .037. The 95% confidence interval indicates that between 14% and 34% of Kayden rental properties are rented to families. Contrary to the claims made by Kayden Real Estate, less than 35% of their properties are rented to families. Researchers suggested that the proportion of Australians who are married has decreased since the 1980s. In a sample of 416 adult Australians, 67.5% were married. While this is lower than the percentage of Australians who were married in the 1980s (71%), a Binomial test shows that the difference is not significant, n = 416, p = .068. The 95% confidence interval indicates that between 63% and 72% of all adult Australians are married. There is insufficient evidence to conclude that the proportion of Australians who are married has changed since the 1980s. 2 Foundations of Statistics_Model_Reports_Assignments Independent samples t-test A researcher hypothesised that the blood cholesterol levels of people who do not exercise regularly would be higher than those of regular exercisers. In a random sample of 78 adults, the average blood cholesterol level of the non-exercisers ( x  247.65mg/dL, s = 33.44mg/dL, n = 43) was higher than the average blood cholesterol level of the people who exercise regularly ( x  189.06mg/dL, s = 35.96mg/dL, n = 35), and an independent samples t-test shows that this difference in mean blood cholesterol level is significant, t(76) = 7.44, p < .001. The 95% confidence interval indicates that the mean blood cholesterol level for people who do not exercise regularly is between 42.9 and 74.3 mg/dL higher than for people who do. As expected, the blood cholesterol levels of non-exercisers are higher than for those people who exercise regularly. A school parent hypothesised that children from Westchester Primary School are better spellers than children from Lockhaven Primary School. In a random sample of 50 children, the mean number of words correctly spelt by the Westchester children ( x  8.20 , s  3.97 , n  25 ) was less than the mean number of words correctly spelt by the Lockhaven children ( x  12.32 , s  4.25 , n  25 ), and an independent samples t-test shows that this difference in mean number of words is significant, t (48)  3.54 , p = .001. The 95% confidence interval indicates that, on average, Westchester children can correctly spell between 2 and 6 less words than Lockhaven children. Contrary to expectations, children from Westchester Primary School are poorer spellers than children from Lockhaven Primary School. It was suggested that drivers in the Northern suburbs use more fuel than those in the Western suburbs. In a sample of 100 drivers, the average fuel consumption for those from the Northern suburbs ( x  43.11 litres, s  7.78 litres, n  50 ) was greater than the average fuel consumption for drivers from the Western suburbs ( x  40.33 litres, s  9.11 litres, n  50 ). However, an independent samples t-test shows that this difference in mean fuel consumption is not significant, t (98)  1.64 , p = .105. The 95% confidence interval indicates that, on average, fuel consumption is between .59 litres less and 6.14 litres more in the Northern suburbs than in the Western suburbs. There is insufficient evidence to suggest that fuel consumption is different for drivers in the Northern and Western suburbs. 3 Foundations of Statistics_Model_Reports_Assignments Non-directional hypothesis reports: On occasions we might not be able to provide a direction for our hypothesis. We just think that something is different – but not sure how! Our reports follow the same format as those shown on the previous pages, with slightly modified wording. The following three reports provide an indication of how you might report on a non-directional hypothesis. These are based on the first report of each hypothesis test from the previous pages [Onesample t-test, Binomial test and Independent samples t-test]. One Sample t-test A study was conducted to investigate if the age of tourists who are travelling to Katatonia now is different to those tourists in 1995. In a random sample of 250 tourists in Katatonia, the average age was 47.77 years (s = 15.41 years). This is higher than the average age of 45 years recorded in 1995, and one-sample t-test shows that this difference in mean age is significant, t(249) = 2.84, p = .005. The 95% confidence interval indicates that since 1995 the average age of tourists is between 0.85 and 4.69 years higher. As expected, the age of tourists in Katatonia now is different to the age of tourists in 1995. On average, the age of tourists is now higher. Binomial test A study was conducted to explore whether the percentage of Australians using a computer at home has changed from census data collected in 2001. In a random sample of 100 adult Australians, 54% had used a computer at home in the previous week. This is higher than the percentage of Australians who reported using a computer at home in the 2001 census (42%), and a Binomial test shows that the difference is significant, n = 100, p = .010. The 95% confidence interval indicates that between 44% and 64% of adult Australians use a computer at home. As expected, the percentage of Australians using a computer at home has changed from the 2001 census data. A higher percentage of Australians now report using a computer at home. Independent samples t-test A researcher hypothesised that the blood cholesterol levels of people who do not exercise regularly would be different from those of regular exercisers. In a random sample of 78 adults, the average blood cholesterol level of the non-exercisers ( x  247.65mg/dL, s = 33.44mg/dL, n = 43) was higher than the average blood cholesterol level of the people who exercise regularly ( x  189.06mg/dL, s = 35.96mg/dL, n = 35), and an independent samples t-test shows that this difference in mean blood cholesterol level is significant, t(76) = 7.44, p < .001. The 95% confidence interval indicates that the mean blood cholesterol level for people who do not exercise regularly is between 42.9 and 74.3 mg/dL higher than for people who do. As expected, the blood cholesterol levels of non-exercisers is different from those of regular exercisers. Blood cholesterol levels for people who do not exercise regularly are higher than for those people who exercise regularly. 4 Foundations of Statistics_Model_Reports_Assignments

Tutor Answer

mickeygabz
School: University of Maryland

Here is the attached answer... You just need to edit the first page with your name and ID

Running head: ASSESSMENT 2 - ANALYSIS OF DATA

Assessment 2 – Analysis of Data
Name: Rhys Luckey
Student ID: 12345678
Swinburne Online

If you are using this template to start your assignment, please make sure you include
your own name and student number above. Additionally, the file name should be
renamed to include your surname and ID number. Once you’ve done this, remove this
text.

1

ASSESSMENT 2 - ANALYSIS OF DATA

2

Assessment 2 – Analysis of data
Question 1 – Summary of a categorical variable
The distribution of the self-assessed health status for a sample of 2000 Australians is
displayed in Figure 1 while the frequency distribution table is shown in table 1. Majority of
the respondents assessed themselves as having Very Good and Good health status at 35.6%
and 31.6% respectively. 17.8% thought that their health was excellent while only 4.4%
thought that their health was poor. 10.6% of the respondents thought that their health was
fair. Overall, majority of Australians believe that their health is good or more than good.
Question 1 – Summary of a categorical variable – SPSS Output

Figure 1: Self-Assessed Health Status
Self-Assessed Health Status
Cumulative
Frequency...

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Anonymous
Outstanding Job!!!!

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