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Data Analysis: Hypothesis Testing
Use the Sun Coast Remediation data set to conduct a correlation analysis, simple regression analysis, and multiple regression analysis using the correlation tab, simple regression tab, and multiple regression tab respectively. The statistical output tables should be cut and pasted from Excel directly into the final project document. For the regression hypotheses, display and discuss the predictive regression equations.
Correlation: Hypothesis Testing
Restate the hypotheses:
Example:
Ho1: There is no statistically significant relationship between height and weight.
Ha1: There is a statistically significant relationship between height and weight.
Enter data output results from Excel Toolpak here.
Interpret and explain the correlation analysis results below the Excel output. Your explanation should include: r, r2, alpha level, p value, and rejection or acceptance of the null hypothesis and alternative hypothesis.
Example:
The Pearson correlation coefficient of r = .600 indicates a moderately strong positive correlation. This equates to an r2 of .36, explaining 36% of the variance between the variables.
Using an alpha of .05, the results indicate a p value of .023 < .05. Therefore, the null hypothesis is rejected, and the alternative hypothesis is accepted that there is a statistically significant relationship between height and weight.
Note: Excel data analysis Toolpak does not automatically calculate the p value when using the correlation function. As a workaround, the data should also be run using the regression function. The Multiple R is identical to the Pearson r in simple regression, R Square is shown, and the p value is generated. Be sure to show your results using both the correlation function and simple regression function.
Simple Regression: Hypothesis Testing
Restate the hypotheses:
Ho2:
Ha2:
Enter data output results from Excel Toolpak here.
Interpret and explain the simple regression analysis results below the Excel output. Your explanation should include: multiple R, R square, alpha level, ANOVA F value, accept or reject the null and alternative hypotheses for the model, statistical significance of the x variable coefficient, and the regression model as an equation with explanation.
Multiple Regression: Hypothesis Testing
Restate the hypotheses:
Ha3:
Ha3:
Enter data output results from Excel Toolpak here.
Interpret and explain the simple regression analysis results below the Excel output. Your explanation should include: multiple R, R square, alpha level, ANOVA F value, accept or reject the null and alternative hypotheses for the model, statistical significance of the x variable coefficients, and the regression model as an equation with explanation.
References
Include references here using hanging indentations. Remember to remove this example.
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Thousand Oaks, CA: Sage.
Rev. 02.03.2019
Rev. 02.03.2019
Discussion Board 1, 2, 3, & 5 Replies Grading Rubric
50 points
Criteria |
Levels of Achievement |
|||
Content |
Advanced |
Proficient |
Developing |
Not present |
Quality of Information Presented in Replies |
32.2 to 35 points Responds to peers in a substantive manner. Responds to any instructor interaction provided within the discussion. |
29.4 to 32.1 points Responds to peers in a substantive manner with minor areas for improvement |
1 to 29.3 points Responds to peers, but responses lack rigor or richness. |
0 points Not Present |
Structure |
Advanced |
Proficient |
Developing |
Not present |
Format and Tone |
4.6 to 5 points Professional vocabulary, writing style and tone are used consistently throughout discussion. Any sources used are properly referenced/cited in APA format. |
4.2 to 4.5 points Professional vocabulary, writing style and tone are used consistently throughout discussion. Any sources used are referenced/cited but have APA formatting errors. |
1 to 4.1 points Several errors exist within professional writing style, tone, and APA citation/reference formatting. |
0 points Not Present |
Participation Quantity |
4.6 to 5 points Responds to more than two peers |
4.2 to 4.5 points Responds to two peers. |
1 to 4.1 points Responds to one peer. |
0 points Not Present |
Word Count for Replies |
4.6 to 5 points A minimum of 150 words was submitted for each reply. |
4.2 to 4.5 points A minimum of 100 words was submitted for each reply. |
1 to 4.1 points A posting less than 100 words was submitted for each reply. |
0 points Not Present |
Discussion Board Forum 3 – Part B
Reply to at least 2 of your classmates' threads, in at least 150 words, building upon the original thread or offering a contrasting viewpoint. The replies must be substantive, and must further the discussion.
Please respond at least 150 words to the following:
Describe the three designs and when is it appropriate to use each design?
Robson and McCartan state that fixed designs are associated with collections of group possessions and with general tendencies (McCartan and Robson, p. 103, 2016). Fixed research designs aren’t given many variables and they take the average of the group rather than the individual outcome. The only variable fixed designs takes into account are the ones that can be measured such as a person, place, thing and/or situation involved. One case study that was conducted involved comparing long working hours to sickness and absence of employees. The fixed research method was used to study utilized date for a specific time period and the employees working there through a merger (Bernstrom, 2018).
When using flexible research design, there are three different research strategies that are utilized, these include case study, ethnographic studies and grounded theory studies (McCartan and Robson, p. 144, 2016). Flexible research design starts with an idea or a specific issue, than through trial and error without any specific predetermined variables. Qualitative outcomes are more likely the result of flexible research design.
A mixed research design is the combination of a fixed and flexible research design that leaves room for more research. Characteristics of a mixed research design, according to Robson and McCartan, include the following:
1. Quantitative and qualitative methods within the same research project.
2. A research design that clearly specifies the sequencing and priority that is given to the quantitative and qualitative elements of data collection and analysis.
3. An explicit account of the manner in which the quantitative and qualitative aspects of the research relate to each other
4. Pragmatism as the philosophical underpinning for the research (p. 177, 2016)
Mixed methods can be thought of as a triangulation based framework for research designs. Mixed methods research focuses on triangulation that spans multiple methodologies (Turner et. Al, 2015).
How are the designs similar?
Both designs allow for qualitative and quantitative research studies.
How are the designs different?
Fixed designs of research don’t allow for many variable involving the study. The studies are compared, usually involving a quantitative answer but the variables are given. Flexible design research allows for all variable and the data collected could change based on said variables.
What specific methods are related to each of the designs?
Fixed designs of research tend to use surveys, interviews, but only specific questions, controlled observations and controlled experiments based off of the research question being asked. Flexible designs of research use many different variable of research, interview, but can sway from the questions based on the answers, uncontrolled environment and focus groups.
Please respond at least 150 words to the following:
Research Design Strategies
One important aspect of doing research is chosing which research design strategy will be utilized (Robson & McCartan, 2016). The three research designs are fixed, flexible, and multi-strategy (Robson & McCartan, 2016).
Fixed
The logic behind fixed designs, is that they are “based on organizing, standardizing, and codifying research into explicit rules, formal procedures, and techniques so others can follow the same linear plan and reconstruct the study” (McGregor, 2018, p. 210). The results are typically used to create a generalization about the group (Robson & McCartan, 2016).
Flexible
The text describes the flexible design as one that elvolves during the process of collecting data (Robson & McCartan, 2016). This design is usually focused almost soley on gathering qualitative data (Robson & McCartan, 2016). This method allows for a bit more deviation from the original research questions (McGregor, 2018).
Multi-strategy
The mutli-strategy design, also know as mixed methods, is a combination of both the fixed and flexible designs (Plano Clark & Ivankova, 2016; Robson & McCartan, 2016). Meaning that this design incorporates both quanitative and qualitative research methods (Plano Clark & Ivankova, 2016; Robson & McCartan, 2016). Byrne (2017) speaks to the idea of triangulation, and how important it is that knowledge is based on more than one “mode of inquiry” (p. 4). It is, however, important to be clear about “which research questions call for the use of which methods (quantitative, qualitative, or both)” (Plano Clark & Ivankova, 2016, p. 47).
Compare and Contrast
The difference between the fixed and flexible designs can be boiled down to the fact that the fixed designs rely heavily on quantitative data, while flexible designs rely heavily on qualitative data (Robson & McCartan, 2016). According to Pultz (2018), a fixed research design can’t accomidate new qualtitative information that a researcher might come across in the research process. The multi-strategy design, however, is a way to take the best of both the fixed and flexible methods and utilize those features as part of the research design (Robson & McCartan, 2016).
Specific Methods
Fixed
Studies associated with a fixed design are are usually experiments where quantitative data is collected in the effort to prove a hypothesis (Byrne, 2017).
Flexible
On the other hand, flexible studies are used to gain insight into opinions, motivations, and reasoning (Byrne, 2017). Typical studies associated with flexible designs are focus groups, case studies, interviews, ethnographic studies, and grounded theory studies (Byrne, 2017; Robson & McCartan, 2016).
Multi-Strategy
Byrne (2017) states that a perfect example for when to use the mixed method would be to find a pattern utilizing a quantitative data collection method, then in turn utilize a qualitative method to find out how applicable that data is.

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