PSY 325 Evaluate Statistical Analyses

PSY 325 Evaluate Statistical Analyses

PSY 325 Evaluate Statistical Analyses

Research Scenario 1

Research Scenario 1 involves finding the effects of a new weight loss supplement. The answers to the prompts are as shown below:

Appropriate null hypothesis: The newly administered weight loss supplement has no significant effect.

Appropriate alternative hypothesis: The newly administered weight loss supplement has a significant effect.

The type of analysis that would be appropriate in answering this research question:  The type of analysis that would be appropriate in answering the research question is correlation analysis because, through correlation analysis, the researcher can compare the impact of the supplement on those who got it and those who did not receive the supplement (Miot et al.,2018). This type of analysis majorly focuses on determining the link or relationship between variables. A correlation is usually represented by numerical numbers, which may indirectly or directly vary based on the nature of the existing relationship (Schober & Vetter, 2020).

The independent and dependent variables in the analysis: The new supplement and placebo are independent variables, while weight is the dependent variable.

Levels of the independent variable: Control and experimental.

Levels of measurement for each variable: new supplement: Nominal, Placebo: Nominal, Weight: Ordinal.

Type 1 error of the study: Type I error would exist in a case where the research finds out that the supplement has a significant effect when it is omitted from the study

Type 2 error of the study: Type II error would exist in a case where the researcher finds out that the supplement has no significant effect when it actually has a significant effect.

Research Scenario 2

Research scenario 2 entails a researcher interested in whether certain memory strategies help people remember information. As such, the answers to the prompts are shown below.

Appropriate null hypothesis: There is no significant difference in the words recalled concerning each of the three categories.

Appropriate alternative hypothesis: There is a significant difference in the words recalled concerning each of the three categories.

The type of analysis that would be appropriate in answering this research question: The most

PSY 325 Evaluate Statistical Analyses
PSY 325 Evaluate Statistical Analyses

appropriate analysis for answering this research question is descriptive analysis (Kemp et al.,2018). The descriptive analysis gives the researcher concise and clear measurements and descriptions for each of the categories (Gravetter & Forzano, 2018). In this research question, descriptions are needed to help in assessing the performance of every memory strategy by evaluating the respondents.

The independent and dependent variables in the analysis. Words and memory strategies are independent variables while remembering is the dependent variable.

Levels of the independent variable: Both the independent variable are experimental levels.

Levels of measurement for each variable: Remembering: ordinal, words: nominal, Memory strategies: nominal.

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Type 1 error of the study: Type I error would occur if the null hypothesis is rejected when all the categories displayed no significant difference.

Type 2 error of the study: This error would occur upon acceptance of the null hypothesis when all the categories exhibit significant difference.

Research Scenario 3

Research scenario three entails a local manufacturing company interested in determining whether their employees are as happy with their jobs as other employees. Therefore, the answers to the prompts are as shown below:

Appropriate null hypothesis:  The employees’ happiness is the same as those of other employees.

Appropriate alternative hypothesis: The employees’ happiness differs from that of other employees.

The type of analysis that would be appropriate in answering this research question: The suitable analysis for this research question is descriptive analysis. Through this analysis, the researcher will be able to get measurements and summaries concerning the company and compare the obtained results with those of other companies. Therefore, descriptive statistics helps in describing the features of the data set and produces sample summaries (Sidel et al.,2018).

The independent and dependent variables in the analysis. The independent variable is employees, while the dependent variable is happiness.

Levels of the independent variable: The level of the independent variable is experimental.

Levels of measurement for each variable: The level of measurement of the employee variable is nominal, while happiness is ordinal (Beatty & Beatty, 2018).

Type 1 error of the study: Type I error would occur if the null hypothesis is rejected when the employees’ happiness is equal to that of the other employees.

Type 2 error of the study: Type II error would occur if the null hypothesis is accepted and the employees’ happiness is different from that of other employees.

References

Beatty, W., & Beatty, W. (2018). Four Levels (Scales) of Data Measurement: It’s All About Information. Decision Support Using Nonparametric Statistics, 17–22. Doi: 10.1007/978-3-319-68264-8_4

Gravetter, F. J., & Forzano, L. A. B. (2018). Research methods for the behavioral sciences. Cengage learning.

Kemp, S. E., Ng, M., Hollowood, T., & Hort, J. (2018). Introduction to descriptive analysis. Descriptive Analysis In Sensory Evaluation, 1–39. https://doi.org/10.1002/9781118991657.ch1

Miot, H. A. (2018). Correlation analysis in clinical and experimental studies. Jornal Vascular Brasileiro17, 275-279. https://doi.org/10.1590/1677-5449.174118

Schober, P., & Vetter, T. R. (2020). Correlation analysis in medical research. Anesthesia & Analgesia130(2), 332. Doi: 10.1213/ANE.0000000000004578

Sidel, J. L., Bleibaum, R. N., & Tao, K. C. (2018). Quantitative descriptive analysis. Descriptive Analysis in Sensory Evaluation, 287-318. https://doi.org/10.1002/9781118991657.ch8