Testing Hypothesis and Properties of Bivariate Relationship

Analytical Methods Module 4: Testing Hypothesis and Properties of Bivariate Relationship Quantitative researchers follow a statistical decision-making process to determine how likely it is that a hypothesized population parameter is true. This process, called hypothesis testing, is the focus of Module 4. Hypothesis development starts with an observation, hunch, educated guess, or anecdotal information about a phenomenon, condition, object, relationship, or other item of interest. In other words, a hypothesis is based on a prediction about the extent to which one event might affect, influence, or cause another. Where does a researcher start relative to gathering and analyzing the necessary evidence that may perhaps support a hypothesis? As discussed in prior modules, the researcher starts with a literature review (to explore what research has been done before) and then they determine a methodology that will allow a sample to be drawn from a study population (e.g., police officers, prosecutors, judges, convicted sex offenders). Other steps involve: Determining variables of interest (independent and dependent) and their levels of measurement; Formulating a null hypothesis (Ho) that predicts no relationship between the variables; Formulating a research hypothesis which is the opposite of a null hypothesis (also called an alternate hypothesis: Ha); and Running statistical tests that produce evidence that may reject a null hypothesis (thus showing statistical support for the research/alternate hypothesis). In this module, you will learn how to execute specific statistical tests in SPSS that will allow you to test hypotheses. Learning Outcomes Explain hypothesis testing as a decision-making process. Differentiate between the research hypothesis and the null hypothesis. Determine probability value (P) and significance level (?) and understand their applications. Test difference between two group means — t-test. For Your Success & Readings Hypothesis testing is at the core of statistical analysis and is a decision-making process involving several steps. Hypothesis testing requires the application of a body of specialized terminologies and concepts including the null and alternative hypotheses, probability level, and significance level which are associated with various statistical tests. As stated earlier, think of a hypothesis as an educated guess or hunch about the relationship between two or more variables—about which statistical data will be collected—that:  allows the researcher to conclude that their educated guess is wrong (i.e., falsification);  allows the researcher to conclude their educated guess is correct or supported with a relatively high degree of confidence (generally speaking, 95% or greater confidence). These terminologies and the ideas they represent may appear unfamiliar to you. The initial difficulties you encounter in understanding them should not intimidate you while learning quantitative analysis. You will gain familiarity with these concepts by applying them in analyzing real data. You may find hypothesis testing growing on you through application. Module 4 walks you through the process of statistical hypothesis testing while you learn one of many statistical tests: the t-test. A Critical Thinking Assignment and Discussion Question are due this week. You may also be invited to participate in a Live Classroom session (hosted by your instructor). Required Chapter 8 in Social Statistics for a Diverse Society Chapter 11 in Online Statistics Education: A Multimedia Course of Study Eisenberg, T. & Heise, M. (2015). Plaintiphobia in state courts redux? An empirical study of state court trials on appeal. Journal of Empirical Legal Studies, 12(1), 100-127. Recommended Knapp, H. (2017). An introduction to the paired t-test [Video file]. SAGE Research Methods. Quiz on hypothesis testing Next References Frankfort-Nachmias, C., & Leon-Guerrero, A. (2017). Social statistics for a diverse society (8th ed.). Thousand Oaks, CA: Sage. Nayak, B. K., & Hazra, A. (2011). How to choose the right statistical test? Indian Journal of Ophthalmology, 59(2), 85-86. ritical Thinking Assignment (120 Points) Important! Read First Choose one of the following two assignments to complete this week. Do not do both assignments. Identify your assignment choice in the title of your submission. Option #1: Inferential Test Criminologists have long studied the relationships between employment opportunity, upward mobility in society and criminality. For this assignment, we will evaluate a study of mobility that was conducted in Netherlands. Read the “Determinants of Intergenerational Downward Mobility in the Netherlands”   (Links to an external site.) article: In a well-organized essay, answer the following questions. Review the assumptions made for each inferential test (based on the information in this chapter). Review the null hypothesis for each inferential test (based on the information in this chapter). How are final statistics (t-obtained, chi-square obtained, or F obtained) reported in the article? Based on the table or summary of final statistics, what conclusions do the authors make? Do they find support for their original hypothesis? Explain your answer. Option #2: Sampling Technique In 2016, Australian researchers conducted a study on the fear of crime, “(Re)assessing Contemporary “Fear of Crime” Measures within an Australian Context.”  (Links to an external site.) Read this study publication and, in a well-organized essay, answer the following questions: Discuss the sampling technique used by the original researchers and why they chose that technique (based on the information in this chapter). Summarize the findings from the statistical tables presented in the textbook (based on the information in this chapter). What final statistics were utilized to determine any correlations? What conclusions do the authors make? Do they find support for their original hypothesis? Explain your answer.

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