Instructions

Use the Quantitative Study Example Project in Resources to complete this assignment.

Complete the following:

    • Business Problem: Formulate a current business problem using examples and descriptions drawn from scholarly literature (attached)
    • State and briefly explain it.
    • Explain the problem’s relationship to the research question.
  2. Research Question: Refine the business problem into one or more research questions that require the use of inferential statistics and allow for an exploratory investigation.
    • From the business problem, explain a research question that will require use of inferential statistics.
    • With each question, address the relationships among variables and/or the difference among groups or conditions.
  2. Variables: Refine the research question into variables that are operational and measurable.
    • Identify the variables that are involved in that research question.
    • Explain the significance and magnitude of the statistical relationships or differences.
  2. Data Collection Instruments: Explain how to evaluate the ability of the instruments or other data collection methods to quantify the variables.
    • Identify the instruments or other data collection methods that will be used to gather the data needed to measure your variables.
    • Explain how these instruments and/or methods will be evaluated to assure their validity and reliability.
  2. Statistical Analysis Technique: Explain how a selected statistical analysis technique is appropriate for a specific research question and the data to be analyzed.
    • Review Table 1: Decision Matrix for Inferential Statistics Selection in Choosing a Statistical Technique (linked in Resources).
    • Using the four-box inferential statistical technique, determine which technique family your statistical analysis technique will come from (Box 1, 2, 3, or 4) using the Decision Matrix for Inferential Statistics Selection.
    • Assume for this assignment that the technique you will use corresponds to the box you chose in Table 2: Decision Matrix Sample Statistics Choice. For example, if applying the logic you learned in this unit, you conclude that the appropriate box is Box 1, assume that your appropriate statistical analysis technique is the Multiple Linear Regression choice.
    • List this choice and briefly explain the logic that led to its selection. If you chose Box 1 or Box 2, also provide a brief statement explaining what you will do if the data you collect do not meet the requirements for the use of parametric statistics.
  2. Minimum Sample Size: Identify the minimum sample size necessary and appropriate input parameters for the previously selected statistical technique and associated test family.
    • Review Table 2: Decision Matrix Sample Statistics Choice in Choosing a Statistical Technique (linked in Resources).
    • Use the G*Power tool downloaded in Unit 3 to estimate the minimum sample size that you will need.
    • Use the “A priori Compute Required Sample Size” setting.
    • Justify the input parameters.

Quantitative Study Example Project

What follows is a hypothetical quantitative study that you can use to set up your U05a1 assignment. The variable data from this example are from an actual study, but the names of participants and variables have been changed. In all other respects, the description is accurate. For this example, imagine that you are researcher who often consults with small to medium size manufacturing companies in Northwest Ohio who make auto parts for the large auto manufacturing companies. You have noticed concern among your clients about the turnover of their line factory workers. In the last year for which data were available (2017) it was determined that the average annual population of motor vehicles manufacturing employees in the State of Ohio during calendar 2017 was 19,600 employees (Bureau of Labor Statistics, 2018), of which about 30% were estimated to be factory line workers or 5,880 workers. A list can be obtained of these employees through a provider of data lists.

You decide to conduct a study to investigate what independent variables might be valuable in predicting employees’ likelihood of leaving their jobs. Suppose that you have reviewed the research literature on the subject and identified a construct called “turnover intention” and found a scale called the Turnover Intention scale that might be used to measure and predict how likely employees are to terminate their employment. Constructs are often explanatory variables that cannot be directly observed. For example, one cannot “see” a turnover intention, but these intentions can be quantified using a survey instrument. This literature review also identified two other constructs that might have value in predicting what employees’ turnover intentions might be. One of these variables is job mastery, a survey instrument scale that measures how well employees believe that they have mastered the skills involved in their jobs. A scale called the Job Mastery scale exists that would allow you to measure this construct. Another variable you identify is a survey instrument used to measure a person’s control of her state, called the Impulse Control scale.

You decide to conduct a study of employees who work as line factory employees of the auto industry in Ohio. You want your study to look at how well the two variables, Job Mastery and Impulse Control, will predict Turnover Intentions. In doing so, you are aware that it is also important to pay attention to the direction of the effects. That is, whether there is a direct effect (an increase in the independent variable leads to an increase in the dependent variable) or an inverse effect (an increase in the independent variable leads to an increase in the dependent variable).