Analyze the data and interpret the results using a MANOVA. Run a t-test using this data and interpret those results. Compare the outcomes of the MANOVA and t-test and identify any differences. Which approach would you use? Why?

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Statistics Topic 6 – MANOVA Project

Directions:Complete this assignment in 500-750 words using the following information:

A researcher randomly assigns 33 subjects to one of three groups. Group 1 receives technical dietary information interactively from an online website. Group 2 receives the same information from a nurse practitioner, while Group 3 receives the information from a video made by the same nurse practitioner.

The researcher looked at three different ratings of the presentation: difficulty, usefulness, and importance to determine if there is a difference in the modes of presentation. In particular, the researcher is interested in whether the interactive website is superior because that is the most cost-effective way of delivering the information.

Group Usefulness Difficulty Importance   Group Usefulness Difficulty Importance
1 20 5 18   2 29 10 5
1 25 9 8   2 26 11 1
1 23 15 20   2 22 5 2
1 16 9 22   2 15 15 14
1 20 6 22   2 29 6 4
1 28 14 8   2 15 6 3
1 20 6 13   3 22 8 12
1 25 8 13   3 27 9 14
1 24 10 24   3 21 10 7
1 18 10 20   3 17 9 1
1 17 9 4   3 16 7 12
2 28 7 14   3 19 9 7
2 25 14 5   3 23 10 1
2 26 9 20   3 27 9 5
2 19 15 22   3 23 9 6
2 29 14 12   3 16 14 22
2 15 6 2          

 

  1. Analyze the data and interpret the results using a MANOVA.
  2. Run a t-test using this data and interpret those results.
  3. Compare the outcomes of the MANOVA and t-test and identify any differences. Which approach would you use? Why?

Explore data collection methods. Include a timeframe for data collection.  Describe how data will be managed. Provide a summary of the main points covered in your project protocol. All claims and opinions should be supported by available evidence.

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Project protocol- nursing/public health

Paper Guidelines for writing and presenting your project protocol.

Throughout, justification / defence of chosen methods should be provided from available literature.

  1. Introduction (approx. 100 words):

Provide a brief outline / signposting to your project protocol.

Introduce your topic, concisely describe your chosen topic, and present your research question (using framework PICOT). – this can be done in a table or schematic design, just make sure the acronym is utilised

  1. Research design and rationale for chosen design. (approx. 600 words):

Depending on the type of study (research design) to be conducted, a different tool/checklist should be used. To assist with research protocol preparation, the following checklists can be used as a template:

Tool / checklist name Hyperlinked abbreviated name Intended study type
Strengthening the Reporting of Observational studies in Epidemiology STROBE checklist Observational studies
Consolidated Standards of Reporting Trial CONSORT Statements Randomised controlled trials
Standards for Reporting Qualitative Research SRQR recommendations Qualitative Research
Standards for Quality Improvement Reporting Excellence SQUIRE guidelines Quality improvement studies

 

  • Setting (approx. 300 words):

This should include details of how participants will be sampled. Inclusion and exclusion criteria. Explore how your will sample be accessed.

  1. Data collection (approx. 300 words):

Explore data collection methods. Include a timeframe for data collection.

Data collection tools presented in an appendix will not be included in assessment word count.

Explore potential ethical considerations.

  1. Data management and analysis (approx. 350 words):

Describe how data will be managed.

Present a data analysis plan.

  1. Potential implications for practice (approx. 250 words):

Present how your intended research will improve practice.

  • Conclusion (approx. 100 words):

Provide a summary of the main points covered in your project protocol. All claims and opinions should be supported by available evidence.

Describe the source(s) of the data and how each variable is measured. Discuss the estimation strategy you adopt, the potential econometric issues that may be relevant and how you plan to deal with them. Discuss any estimator, tests and approaches you intend to apply to support your arguments in your analysis.

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An empirical project – Impact of venture capital on financial market development”

Section III: The Data and methodology

• Describe the source(s) of the data and how each variable is measured.

• Provide an exploratory data analysis. Point out any salient features of the data and describe any interesting pattern/ correlation in the data. Provide summary statistics and discuss your findings.

• Specify the regression model, and discuss why such a specification is adopted, for example, why each of the explanatory variables is included, and describe their anticipated effect (either based on theory, previous empirical work, or your rationale). A formal presentation of an empirical model with full explanation of your notation is expected.

• Discuss the estimation strategy you adopt, the potential econometric issues that may be relevant and how you plan to deal with them. Also discuss any estimator, tests and approaches you intend to apply to support your arguments in your analysis.

Section IV: Econometric results

• Properly present the econometric estimates and evaluate the model performance in terms of goodness of fit and diagnostic tests.

• Interpret the estimated coefficients, and describe whether they correspond to your expectations in light of the literature/theories
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• Discuss the results of other specification tests, hypothesis tests, robustness analysis (if you have conducted any) and report your findings.

• Does the estimated equation support the theory on which it is based or the rationale in your mind? What explains any discrepancy between theory and empirics?

• How do the results compare with existing findings? What new insights your results have added?

• You should put your results in a table; here you should follow the approach used in peer reviewed research papers.

Note : specify why we choose a certain regression model and why we choose a certain estimation model (pooled OLS , fixed , Random Effect)

Is there a significant difference between the academic tracks on average student height? Explain. Provide a full interpretation of the results. Is there a difference between the number of hours students study and the hours they work?

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QUANTITATIVE ANALYSIS: COMPARING GROUPS WITH T TESTS, ANALYSIS OF VARIANCE (ANOVA) AND SIMILAR NON-PARAMETRIC TESTS

Using the CollegeStudentData.sav file, do the following problems. Print your outputs after typing your interpretations on them. Circle the key parts of the output that you use for your interpretation.

9.1 Is there a significant difference between the academic tracks on average student height? Explain. Provide a full interpretation of the results.

9.2 Is there a difference between the number of hours students study and the hours they work? Also, is there an association between the two?

9.3 Write another question that can be answered from the data using a paired sample t test. Run the t test and provide a full interpretation.

9.4 Are there differences between fast track and regular track students in regard to the average number of hours they (a) study, (b) work, and (c) watch TV? Hours of study is quite skewed so compute an appropriate nonparametric statistic.

The problems require the use of “academic track.” This variable is not in the data set given (CollegeStudentData.sav).  To resolve this, you may pick any variable you want in the data set as a substitute.

What is the prevalence rate of some diseases in Suba County? What is the incidence rate of some diseases in Suba County? Is there a significant difference between prevalence and incidence rates in Suba County?

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Research Hypothesis (Relative Measures of Disease Frequency)

Abstract
Suba county in Uganda is the study focus area. It has an ingenious population fit for health and medical research owing to its diversified age groups, culture, education levels and civilisation. Suba has 4 sub counties. Level 5 hospitals were key to establishing frequency of diseases (malaria, TB, HIV & AIDS) in the population. The study was invoked by previous researchers who have recorded measures of frequency (prevalence and incidence rates) of disease associated factors. The study shall compare prevalence and incidence rates in four hospitals in Suba and find out if there is any significant difference between them. Data was analysed in excel software.
Keywords: prevalence, incidence, disease burden, significant difference

The study of disease existence and its causative agents is the main focus of epidemiologists (saha et al., 2008). Occurrence or frequency of disease among sections of the population is a dynamic process. Subgroups of the population keep changing and so do prevalence and incidence rates of diseases. However, it is this dynamism that enables researchers to identify possible causes and factors that accelerate a disease. Possible curative and preventive measures can be invented.
This study intends to investigate the prevalence and incidence of some select diseases in Suba County hospitals. The investigation will help answer the question of whether the prevalence and incidence rates are the same throughout the study area or not. Prevalence is the real or actual status of a disease in the population of interest. It may be thought as the section of the population that has already been infected by a disease. It is usually calculated as a fraction of the infected persons to the population. Incidence refers to the number of new infections of a disease in a certain time period (Noordzij et., al 2013).

Objectives
i. To investigate the prevalence rate of select diseases in Suba County
ii. To investigate the incidence rates of some diseases in Suba County
iii. To investigate whether there is a significant difference between the prevalence and incidence rates in Suba County

Research questions
i. What is the prevalence rate of some diseases in Suba County?
ii. What is the incidence rate of some diseases in Suba County?
iii. Is there a significant difference between prevalence and incidence rates in Suba County?

Do a stem-and-leaf plot for the same-sex parent’s height split by sex at birth. Discuss the plots. Which variables are nominal? Run Frequencies for the nominal variables and other variables with fewer than five levels. Comment on the results. Do boxplots for student height and for hours of study. Compare the two plots.

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SPSS Problems

Chapter 4

Using the College Student Data.sav file (see Appendix A), do the following problems. Print your outputs and circle the key parts of the output that you discuss.

4.1.For the variables with five or more ordered levels, compute the skewness. Describe the results. Which variables in the dataset are approximately normally distributed/scale? Which ones are ordered but not normal?

4.2.Do a stem-and-leaf plot for the same-sex parent’s height split by sex at birth. Discuss the plots.

4.3.Which variables are nominal? Run Frequencies for the nominal variables and other variables with fewer than five levels. Comment on the results.

4.4.Do boxplots for student height and for hours of study. Compare the two plots. Make Sure to:

1. Attach your word document for review and grading. Other file formats are not accepted and will not be graded. Use the following filename format:

2. Include an APA title block with your name, class title, date, and the assignment number.

3. Include a table of contents and a reference section. Number your pages in the footer along with the date. Include a header starting on page 2 with the Course and assignment number.

4. Write the problem number and the problem title as a level one heading (Example ‐ A.1.1: Chapter 2, Problem 2.1, and then provide your response.

5. Use level two headings with short titles for multi part questions (Example ‐ A1.1.a, Short Title, A1.1.b, Short Title II, etc.)

6. Use appropriate level headings for key elements of your discussion such as Research Questions, Hypotheses, Descriptive Statistics, Assumptions & Conditions, Interpretation, Results, and others. Your goal is to make your analysis easy to follow and logical.

7. Ensure that all tables and graphs are legible and include a figure number.

8. Carefully review your document prior to submission for formatting, flow, and readability. Keep in mind that running the statistical tests is only the first half of the challenge; you must be able to clearly communicate your findings to the reader.

If you have categorical, ordered data (such as low income, middle income, high income) what type of measurement would you have? Why? Compare and contrast nominal, dichotomous, ordinal, and normal variables. (b) In social science research, why isn’t it important to distinguish between interval and ratio variables?

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Variables, Z Scores, Population and Output

The student will complete 8 short-answer discussions in this course and 1 long-answer Integrating Faith and Learning discussion. In the thread for each short-answer discussion the student will post short answers to the prompted questions. The answers must demonstrate course-related knowledge and support their assertions with scholarly citations in the latest APA format. Minimum word count for all short answers cumulatively is 200 words. The minimum word count for Integrating Faith and Learning discussion is 600 words. For each thread the student must include a title block with your name, class title, date, and the discussion forum number; write the question number and the question title as a level one heading (e.g. D1.1 Variables) and then provide your response; use Level Two headings for multi part questions (e.g. D1.1 & D1.1.a, D1.1.b, etc.), and include a reference section. Respond to the following short answer questions from Chapter Three in the Morgan, Leech, Gloeckner, & Barrett textbook:

If you have categorical, ordered data (such as low income, middle income, high income) what type of measurement would you have? Why?

D2.3.2. (a) Compare and contrast nominal, dichotomous, ordinal, and normal variables. (b) In social science research, why isn’t it important to distinguish between interval and ratio variables?

D2.3.3. What percent of the area under the standard normal curve is within one standard deviation of (above or below) the mean? What does this tell you about scores that are more than one standard deviation away from the mean?

D2.3.4. (a) How do z scores relate to the normal curve? (b) How would you interpret a z score of –3.0? (c) What percentage of scores is between a z of –2 and a z of +2? Why is this important?

D2.3.5. Why should you not use a frequency polygon if you have nominal data? What would be better to use to display nominal data?

Create bar charts. Discuss why you did or did not create a bar chart for each variable. Create histograms. Discuss why you did or did not create a histogram for each variable. Create frequency polygons. Discuss why you did or did not create a frequency polygon for each variable. Compute the range, standard deviation, and skewness. Discuss which measures of variability are meaningful for each of the four variables.

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QUANTITATIVE ANALYSIS: MEASUREMENT AND DESCRIPTIVE STATISTICS

Chapter 3
Use the hsbdata.sav file to do these problems with one or more of these variables: math achievement, mother’s education, ethnicity, and academic track. Use Tables 3.2, 3.3, and the instructions in the text to produce the appropriate plots or descriptive statistics. Be sure that the plots and/or descriptive statistics make sense (i.e. that they are a “good choice” or “OK”) for the variable.

3.1. Create bar charts. Discuss why you did or did not create a bar chart for each variable.

3.2. Create histograms. Discuss why you did or did not create a histogram for each variable.

3.3. Create frequency polygons. Discuss why you did or did not create a frequency polygon for each variable. Compare the plots in Extra SPSS Problems 3.1, 3.2, and 3.3.

3.4. Compute the range, standard deviation, and skewness. Discuss which measures of variability are meaningful for each of the four variables.

3.5. Compute the mean, median, and mode. Discuss which measures of central tendency are meaningful for each of the four variables.

Make Sure to:

1. Attach your word document for review and grading. Other file formats are not accepted and will not be graded. Use the following filename format:
LastName_BUSI820_AssignmentX.docx

2. Include an APA title block with your name, class title, date, and the assignment number.

3. Include a table of contents and a reference section. Number your pages in the footer along with the date. Include a header starting on page 2 with the Course and assignment number.

4. Write the problem number and the problem title as a level one heading (Example ‐ A.1.1: Chapter 2, Problem 2.1, and then provide your response.

5. Use level two headings with short titles for multi part questions (Example ‐ A1.1.a, Short Title, A1.1.b, Short Title II, etc.)

6. Use appropriate level headings for key elements of your discussion such as Research Questions, Hypotheses, Descriptive Statistics, Assumptions & Conditions, Interpretation, Results, and others. Your goal is to make your analysis easy to follow and logical.

7. Ensure that all tables and graphs are legible and include a figure number.

8. Carefully review your document prior to submission for formatting, flow, and readability. Keep in mind that running the statistical tests is only the first half of the

Explain the sample size, sampling method, and measurement methods you might use to have collected the mock data for your study.  Explain the descriptive statistics and charts which you might use to first analyze the data and check the sample for outliers and normality.

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Screen Cast videos 12.8 and 12.8.2

Preparation

To prepare for this discussion, follow along with our Screen Cast videos 12.8 and 12.8.2 to make sure you can generate all of the required results.

Required SPSS Videos

    1. Stats 3e Screencast 12.8 (shows how to get a One-Way Anova from the “compare means” menu)
    2. Stats 3e Screencast 12.8.2 (shows how to get the same results but from the GLM (general linear model) menu)
      1. This should be further evidence that Anova is a special case of the general linear model.  You will learn more about that later in our class.
      2. Pay special attention to the mention of the “power” result which is available through the GLM command and which our speaker notes is an estimate of what percent of samples would yield a significant result IF there was a true effect in the population.  This is interesting because in the video example, that percent is about 61, which is relatively low power
    3. Use this NICE video (click here) to see how to calculate EFFECT SIZE for the One-Way Anova (Eta squared, partial Eta Squared).  This will also require that you use the steps in video 12.8.2 as the way to generate your One-Way Anova
Optional papers and videos for interpreting SPSS One Way Anova output tables
  1. [Paper] Analysis of variance (ANOVA) comparing means of more than two groups” (click here)
  2. There are any number of youtube videos for interpreting One-Way Anova tables, so if you want to hear more, go to Youtube and take your pick.  Videos use different versions of SPSS, but the main theory for reading the ouptut is the same.
  3. A power-point presentation (click here) on running and interpreting One-Way Anova in SPSS

Mini-Report Instructions

Welcome to our third mini-report.  Now that you have some practice writing these reports, we will add in tthree new features.

  • The concept of operational definitions (a review from our first few weeks of class)
  • The concept of post-hoc testing which is required for any One-Way Anova that has three or more “levels” of the independent variable
  • Note the measures of effect size and statistical power which come with the output tables. Where are these values and what do they mean?

This week we will use the same mini-report format you learned last week to explore the One-Way Anova. The point of a mini-report format is to build your ability to take a research question from start to finish, from creating the question and phrasing it as a testable hypothesis to choosing the right statistical test, generating the results and sharing those results in an APA formatted mini-report.  These mini-reports follow the layout of a typical journal article so you should be seeing that too.

  • Our goals here are the same as last week except that you will need to come up with a scenario in which you COMPARE AMONG 3 OR MORE GROUP MEANS.
  • Here, you will create a mock study and write up the results as a mini-paper.
  • You may use the scenario you thought up in the first discussion of the week, based on Paul Bloom’s TED.com talk, or you can use a different example.
  • We are going to share these mini-reports with each other as a discussion so everybody will be able to see each others’ examples and therefore have a better idea of how to run statistical tests and write up the results.  If you are stumped on how to write your post, look at what others have written but change the example hypothesis to one which interests you.

To complete this assignment, you are asked to generate a scenario that would require the use of a One-Way Anova, write your research question and matching hypothesis, generate fake/mock data, enter that correctly into SPSS, calculate and explain your results.  It would be best to write your replies in MS word, save them, and paste them into this discussion so you don’t lose any work.

The sections of this mini-report are
  1. Title
  2. (2 points) Brief introduction to the scenario (explain what you are comparing, what the variables are and what your null and alternative hypotheses are.
    1. List the independent variable’s name ____ how many levels it has _____ and what those levels are ______.  See this link if you are stumped. https://www.statisticshowto.datasciencecentral.com/probability-and-statistics/hypothesis-testing/anova/
      1. Provide an operational definition for the independent variable (yes, even categorical independent variables need operational definitions).
    2. List the dependent variable’s name and its operational definition_____.  Is this an interval or ratio scale measurement?
  3. (3 pts) Brief explanation of the methods
    1. explain the sample size, sampling method, and measurement methods you might use to have collected the mock data for your study.  Use about 20-30 data points per group.
    2. explain the descriptive statistics and charts which you might use to first analyze the data and check the sample for outliers and normality
    3. list your choice of alpha level and explain that choice.  Will you use the standard p<.05 level or a different criterion and why?
    4. Explain what post-hoc tests you used and why they were used.
  1. (3 pts) Results [Hint, see: this power-point presentation (click here) on running and interpreting One-Way Anova in SPSS]
    1. List the descriptive statistics for your data.  List any charts which accompany them.
    2. Paste in the Anova results table for your data
    3. Report the descriptive statistics (means and standard deviations) and the inferential statistics (One-Way Anova results) in APA format. http://statistics-help-for-students.com/How_do_I_report_a_1_way_between_subjects_ANOVA_in_APA_style.htm
    4. Explain whether or not you rejected the null hypothesis and why

Use this NICE video (click here) to see how to calculate EFFECT SIZE for the One-Way Anova (Eta squared, partial Eta Squared).  This will also require that you use the steps in video 12.8.2 as the way to generate your One-Way Anova

Create bar charts. Discuss why you did or did not create a bar chart for each variable. Create histograms. Discuss why you did or did not create a histogram for each variable. Create frequency polygons. Discuss why you did or did not create a frequency polygon for each variable. Compute the range, standard deviation, and skewness. Discuss which measures of variability are meaningful for each of the four variables.

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QUANTITATIVE ANALYSIS: MEASUREMENT AND DESCRIPTIVE STATISTICS

Chapter 3
Use the hsbdata.sav file to do these problems with one or more of these variables: math achievement, mother’s education, ethnicity, and academic track. Use Tables 3.2, 3.3, and the instructions in the text to produce the appropriate plots or descriptive statistics. Be sure that the plots and/or descriptive statistics make sense (i.e. that they are a “good choice” or “OK”) for the variable.

3.1. Create bar charts. Discuss why you did or did not create a bar chart for each variable.

3.2. Create histograms. Discuss why you did or did not create a histogram for each variable.

3.3. Create frequency polygons. Discuss why you did or did not create a frequency polygon for each variable. Compare the plots in Extra SPSS Problems 3.1, 3.2, and 3.3.

3.4. Compute the range, standard deviation, and skewness. Discuss which measures of variability are meaningful for each of the four variables.

3.5. Compute the mean, median, and mode. Discuss which measures of central tendency are meaningful for each of the four variables.

Make Sure to:

1. Attach your word document for review and grading. Other file formats are not accepted and will not be graded. Use the following filename format:
LastName_BUSI820_AssignmentX.docx

2. Include an APA title block with your name, class title, date, and the assignment number.

3. Include a table of contents and a reference section. Number your pages in the footer along with the date. Include a header starting on page 2 with the Course and assignment number.

4. Write the problem number and the problem title as a level one heading (Example ‐ A.1.1: Chapter 2, Problem 2.1, and then provide your response.

5. Use level two headings with short titles for multi part questions (Example ‐ A1.1.a, Short Title, A1.1.b, Short Title II, etc.)

6. Use appropriate level headings for key elements of your discussion such as Research Questions, Hypotheses, Descriptive Statistics, Assumptions & Conditions, Interpretation, Results, and others. Your goal is to make your analysis easy to follow and logical.

7. Ensure that all tables and graphs are legible and include a figure number.

8. Carefully review your document prior to submission for formatting, flow, and readability. Keep in mind that running the statistical tests is only the first half of the