PSY 87540 California Southern University Happiness Statistical Methods and Analysis Paper I have completed the paper as shown in Knach file. What I need is

PSY 87540 California Southern University Happiness Statistical Methods and Analysis Paper I have completed the paper as shown in Knach file. What I need is this:The part in red is the part I don’t honestly know how to explain. Any assistance would be appreciated! I haven’t added the reference section yet but otherwise it is basically done.. The data was provided by my Mentor in class Our task is to proof read the paper and answer the red part only. 1
Final Research Report
Your Name Here
California Southern University
PSY87540: Statistical Methods and Analysis
Professor’s Name Here
Due Date Goes Here
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Abstract
The first line of the abstract is not indented. An abstract summarizes, usually in one
paragraph of 300 words or less, the major aspects of the entire paper in a prescribed sequence
that includes: 1) the overall purpose of the study and the research problem(s) you investigated; 2)
the basic design of the study; 3) major findings or trends found as a result of your analysis; and,
4) a brief summary of your interpretations and conclusions. Here is an example of an abstract:
The purpose of this study is to examine The purpose of this study is to determine if the theory of
reasoned action (TRA) and the theory of planned behavior (TPB) can retroactively predict
whether fraternity men communicate sexual consent to their partner. Fraternity men (n = 177)
completed a survey measuring their attitudes, subjective norms, perceived behavioral control,
behavioral intentions, and actual sexual consent behavior during the 30 days prior to completing
the survey. Results indicated that fraternity men have overall positive attitudes, subjective
norms, perceived behavioral control, and behavioral intentions. A path analysis indicated that
the TPB model had overall more predictive power for this target audience and behavior. Practical
application for health professional are discussed, specifically the implications for developing
messages to target this behavior in this population.
Keywords: sexual assault, sexual consent, theory of reasoned action, theory of planned
behavior, fraternity
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Final Research Report
Introduction
The introduction leads the reader from a general subject area to a particular topic of
inquiry. It establishes the scope, context, and significance of the research being conducted by
summarizing current understanding and background information about the topic, stating the
purpose of the work in the form of the research problem supported by a hypothesis or a set of
questions, explaining briefly the methodological approach used to examine the research problem,
highlighting the potential outcomes your study can reveal, and outlining the remaining structure
and organization of the paper.
Abbreviated Literature Review
In this short section (1-3 paragraphs) you will want to review at least three books,
scholarly articles, and/or any other sources relevant to a particular issue/area of research. You
will provide a description, summary, and critical evaluation of these works in relation to the
research problem being investigated. This section provides an overview of sources you have
explored while researching your particular topic and demonstrates to your readers how your
research fits within a larger field of study.
Hypotheses
Given the research investigated and reviewed above, this study will examine the
following hypotheses.
H1: Here you will list your hypothesis (or hypotheses). I provide some examples below.
H2: Income (ratio/continuous) will differ based on participants’ sex (nominal/2 groups)
(t-test).
H3: Dependency (ratio/continuous) will differ based on participants’ relationship status
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(nominal/4 groups) (ANOVA).
H4: There is a relationship between income (ratio/continuous) and risk-taking
(ratio/continuous) (Pearson correlation)
H5: There is a relationship between financial comfort (nominal/2 groups) and level of
education (nominal/7 groups) (Chi-square)
Example of hypotheses for 2-way ANOVA (there will always be THREE):
H1: Risk-taking will differ based on participants’ gender.
H2: Risk-taking will differ based on participants’ relationship status.
H3: There is an interaction between gender and relationship status on risk-taking.
Method
Participants
In this section of your project, you will want to include descriptive statistics about the
sample, using the different demographic information and other relevant variables in the data
set. The purpose of this is to describe the sample. You want to think about the variable and its
level of measurement before you choose what measure of central tendency to report. Some
variables that you might want to consider from our data set include: gender, age, financial
comfort, income, education, type of relationship, and marital status. I provide a quick guide
below to help you know which measure of central tendency to use based on the level of
measurement of the variable (see variable names_label_level of measurement.doc).
For NOMINAL level variables, you want to report the mode. It would be helpful to
include the percentage of the sample that is included in each group. For instance, you might
have 30 women (30%) and 70 men (70%) in your sample.
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For INTERVAL and/or RATIO level variables, you want to report the mean AND the
standard deviation.
For any data that may be skewed, you can ALSO report the median with the mean and
standard deviation. For instance, “participants reported a mean income as $32,000 (SD = $4300,
Median = $30,000).
Here is a sample write up for descriptive statistics:
The sample included both males (n = 396; 48.1%) and females (n = 423; 51.3%), who
identified predominately as heterosexual (92.6%). Participants identified as freshmen (44.9%),
sophomores (18.8%), seniors (17.8%), juniors (17.4%), and six students (.7%) did not report
their year in school. Participants identified their ethnicity as non- Hispanic (80.5%) or Hispanic
(18.8%), with 6 people not reporting their ethnicity (.7%). Participants identified their race as
White or Caucasian (67.7%), Asian or Asian American (12.0%), two or more races (9.1%), other
(5.7%), Black or African American (3.0%), American Indian or Alaskan Native (1.0%), Native
Hawaiian or Pacific Islander (.4%), and 9 participants did not identify their race. Participants
ranged in age from 18-49 (M = 20.01; SD = 4.17). Participants reported relationship status as
single and not dating or hanging out with someone (37.3%), in a relationship and not living
together (25.8%), single but casually seeing someone/dating/hanging out with someone (24.8%),
living together but not married (7.8%), other relationship status (2.1%), married (1.7%), and 5
people did not report their relationship status (.6%).
Results
In the following examples, I have highlighted the portion of the write-up that you will
delete and replace with your own content (including variables you tested, means, standard
deviations, test statistics, etc.). This is NOT plagiarism if you use these. In fact, I would rather
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you use these write ups so that you can learn the correct way to write up and articulate your
results.
You will want to include a SEPARATE write up for EACH of the tests that you
perform. You are only required to have one hypothesis (and therefore run one test), however I
would encourage you to have more than one. For instance, if you run a t-test looking at risktaking (DV) and gender (IV), and a correlation with income and risk-taking, you would want to
include two SEPARATE SHORT paragraph write-ups (see below how to do the write up).
H1: t-test
An independent samples t-test was run to test for the sex (IV) effect on employee
performance (DV). The results of this test indicated that men scored significantly higher (M =
76.25, SD = 7.47) than women (M = 71.61, SD = 9.52), t(68) = -2.27, p < .05. The effect size is medium (Cohen’s d = .54). This tells us that the men performed significantly better on the performance test. H2: ANOVA A one-way ANOVA was used to test for the group training (IV) effect on performance (DV). The test was significant. The test revealed a significant effect on performance, F(2, 67) = 20.08, p < .05, effect size = .03). In order to probe group differences, Tukey’s post hoc test was performed. Post-hoc tests revealed a significant difference in performance such that both Group 2 [Skype] (M = 74.35, SD = 8.91) and Group 3 [Combo] (M = 80.12, SD = 4.65) scored signifcantly higher than Group 1 [in-person] (M = 67.06, SD = 7.10). In addition, Group 3 [combo](M = 80.12, SD = 4.65) scored significantly higher than Group 2 [in-person] (M = 74.35, SD = 8.91). This indicates that Skype training and Combination (in person and online) training is better than in person training. It also indicates that the combination training is better than 7 Skype. So, overall in order to get the best performance scores, we want to employ a training that combines in person AND online training. H3: Correlation A Pearson correlation was used to test for the relationship between income and age. The correlation was strong, positive, and significant, r = .84, p < .05, r 2 = .67. H4: Chi-square In order to see if men and women differed in the type of FWBR that they subscribe to, a chi-square was run. Results indicated no significant differences between groups, 2 (6) = 7.69, p = .26, Cramer’s V = .20. *This was not a significant interaction. If it were, the next step, as author, would be to describe what you see using the eye test. Where do frequencies appear to differ? Where do they stay the same? That distinction is yours to make. Discussion The purpose of the discussion is to interpret and describe the significance of your findings in light of what was already known about the research problem being investigated and to explain any new understanding or insights that emerged as a result of your study of the problem. The discussion will always connect to the introduction by way of the research questions or hypotheses you posed and the literature you reviewed, but the discussion does not simply repeat or rearrange the first parts of your paper; the discussion clearly explain how your study advanced the reader's understanding of the research problem from where you left them at the end of your review of prior research. You could separate this based on each hypothesis. This way you would clearly interpret the findings for each one and link what was found back to your 8 introduction and literature review. You can also include practical implications (if any) and future directions (what you would suggest be researched in the future). 9 References Barker, P., and Tyler, S. J. (2020). Predicting fraternity men’s communication of affirmative sexual consent: A test of the theories of reasoned action and planned behavior. Applied Communication Research, 4(5), 444-481. doi: 10.38475.73662.12 Smith, L. C., Stark, P., and Reichter, S. T. (2019). Examining relationship satisfaction and the role of sexual communication between partners. Journal of Communication, 3(4), 564580. doi: 10/48573.3485773.92 Read and Study Chapters 10 and 11 of Statistics for the Behavioral Sciences. Assignment 5 Begin Final Research Report: Write a brief research report (up to about 7 pages, not including title page, abstract, and references on an analysis of the data file. Choose a hypothesis, cite at least three references to justify your hy test your hypothesis with an analysis of the DATA540.SAV file, and then report and discuss the resul results should include both descriptive and inferential statistics. Please make sure your report is submitted by the due date to ensure ample time for mentor feedback, and possible integra feedback and revision if necessary. This report is due in Week 7. Use APA format, including an introduction, abstract, method, results, and discussion section. Please r APA manual: American Psychological Association (2020). Publication manual of the American Psycholo Association. (7th ed.). Washington, D.C. For more detailed information, refer to the instructions for the Research Report Assignment that is lo under the course Resources tab. Assignment Outcomes Consider the implications of using various methodological approaches Determine the appropriate application and interpretation of statistics 1 Final Research Report Julia Knach California Southern University PSY87540: Statistical Methods and Analysis Dr. Lori Bednarchik July 20, 2020 2 Abstract The purpose of this study is to examine the relationship between levels of education and relationship happiness. There have been many studies done on the level of education and overall satisfaction of life; however, not as many studies have been done on the relationship between education level and relationship happiness. The few studies that have been done indicate that college students, in particular college educated women, are more likely to have a longer lasting, happier relationship (Musick, Brand, & Davis, 2012, Weng, 2015, and Mihalcea, Iliescu, & Dinca, 2013). Data was provided by the course Mentor using an internet source. Results indicated a positive weak correlation between education levels and relationship happiness. A regression analysis indicates that there is a small relationship between relationship happiness and education level. The results are discussed along with strategies to further investigate the relationship between education and relationship satisfaction. Keywords: education, happiness, relationships 3 Introduction Happiness is defined as a state of well-being or contentment, or a pleasurable or satisfying experience (Merriam Webster Dictionary, nd). Happiness is a concept that has been difficult to define on both a global and individual level. One’s subjective happiness is different from another person’s subjective happiness, and the factors that influence this difference are not always easy to explain. Science has long been interested in what makes individuals happy. The Organization for Economic Co-operation and Development (OECD) met in November 2018 to discuss the need to develop a scale strictly for happiness, stating that the gross domestic product fails to represent levels of well-being (Kyonne, 2019). The World Happiness Report ranks countries based on a personal and singular concept question about happiness (Kyonne, 2019). Researchers have used several synonyms as a way to describe relationship satisfaction, including marital quality, success, happiness, compatibility, and companionship (Nwafor, 2016). About half of first marriages in the United States are able to survive 20 years, and research has proven that college educated women have an almost eight in ten chance of still being married after 20 years (Weng, 2015). This level drops to 48% for women who have a high school education or less (Weng, 2015). Much of the research based on individual levels of happiness come from the study of governments, their levels of expenditure, corruption, unemployment, inflation rates, taxes, and income tax (Kyonne, 2018); however, at an individual level, there is no significant research on what makes an individual happy. There has been much research on an individual’s level of satisfaction in life and how educational levels influence their rates of happiness. The purpose of this paper is to examine the relationship between levels of education and relationship happiness. The research data in this 4 study were provided for the investigator by her Mentor and included an equal number of men and women. Literature Review In a study conducted by Mihalcea, Iliescu, and Dinca (2013), the authors investigated the levels of influence a couple’s educational levels have on how they rank their relationship satisfaction. The authors studied couples from Romania and used the Dyadic Adjustment Scale to evaluate their quality of their marital relationships. The results from this study indicated that when individuals have graduated from a University, their levels of understanding the importance of factors such as money, religion, and time spent together predicted greater satisfaction in relationships. The inverse was found, poorer and lower educated individuals were associated with denying unmarried relationships and preferring marriage. Musick, Brand, and Davis (2012) investigated the variance in the relationship between education and marriage. The authors investigated how diversity in schools’ influences marriage formation among individuals. The researchers used data from the 1979 National Longitudinal Survey of Youth and found a statistically significant positive trend in effects of college attendance, with the largest positive increase seen in higher levels of education and lower positive effects seen in lower levels of education. Cruz, Abalos, and Cruz (2016), investigated the difference in spouse age and education in marriage satisfaction and health in older individuals. The data came form the 2007 Philippine Longitudinal Study of Aging and found there was no significant difference among Filipino older individuals according to their income and no significant difference in marital satisfaction and the difference in age or education. 5 Finally, Nwafor (2016) investigated the influence of couple’s educational achievement on marital satisfaction. The author used participants from five different faculties at the University of Nigeria and used the Marital Satisfaction Scale. The results from this study indicated that educational attainment of a spouse did significantly influence marital satisfaction. Hypotheses Given the research investigated and reviewed above, this study will examine the following hypotheses. H1: Relationship happiness will not differ depending on education level. H2: Relationship happiness will differ depending on education level Method Participants The sample included both males (n = 200; 20%) and females (n = 200; 50%), who identified predominately as being married (59.3%) verses single (40.8%). The mean for relationship happiness was 3.9 with a standard deviation of 1.030. Relationship happiness was ranked as well with individuals reporting being very unhappy (4.0%), unhappy (4.0%), mixed (22.8%), happy (37.0%), and very happy (32.3%). The type of relationship ranged from dating several people (2.3%), dating one person (13.0%), long-term committed relationship (25.5%), and married (59.3%). Participants age ranged from 21 years old to 63 years old. Participants educational status ranged from no high school (0.8%), high school graduate (8.5%), some college (32.3%), College graduate (29.0%), some graduate school (8.5%), MA/MS (15.3%), and doctorate (5.8%). The 6 mean for education was 4.05 with a standard deviation of 1.4. Data was collected between the years 2004 to 2007. Results H1: Analysis of Regression A linear regression (test of association) was run to test for the influence of education level (IV) on relationship happiness (DV). The test was significant, F (5.509), sig.= 0.019. Model Summary Model R .117a 1 R Square Adjusted R Std. Error of the Square Estimate .014 .011 1.02458 a. Predictors: (Constant), Education ANOVAa Model 1 Sum of Squares Regression df Mean Square 5.783 1 5.783 Residual 417.807 398 1.050 Total 423.590 399 F 5.509 Sig. .019b a. Dependent Variable: Relationship happiness b. Predictors: (Constant), Education H2: Correlation A Pearson correlation was used to test for the relationship between education and relationship happiness. The correlation was weak, positive, and significant, r = .117, p < .05, r2 = .014. 7 Correlations Relationship Education Education Pearson Correlation 1 Sig. (2-tailed) .117* .019 N Relationship happiness happiness 400 400 Pearson Correlation .117* 1 Sig. (2-tailed) .019 N 400 400 *. Correlation is significant at the 0.05 level (2-tailed). Discussion There are many factors that influence relationship happiness, including educational levels, socioeconomic status, government influence, and overall general satisfaction in life. One of the main draw backs to the study of happiness is the inability of different tests to include an individual specific criteria question, regardless of outside influences or cultural diversity. The above research adds to the current research field noting that educational levels do have a small but significant effect on relationship happiness. The null hypoth... Purchase answer to see full attachment