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Choose Your Own Question Come up with your own question you would like to be able to answer. What is the question? How might you collect data to answer this question? What would the cases be? What would the variable(s) be?

Short Answer

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Question: 'Does the color of a product influence a customer's choice?'. The data can be collected through a study where customers choose a product from a selection of same products in different colors. Each customer will serve as an individual case. There are two variables: the color of the product, and the customer's choice.

Step by step solution

01

Defining the Question

Craft a question that intrigues you. For instance, one might ask, 'Does the color of a product influence a customer's choice?' This question allows next steps such as data collection and analysis to move forward.
02

Data Collection Method

Discuss potential ways to gather data. In this case, a hypothetical method could involve conducting a study where customers are presented with the same product in multiple colors and asked to choose one. Their choices would be recorded, providing raw data.
03

Identifying the Cases

Specify what the cases are in your study. In this instance, each customer evaluated would serve as individual case for this study.
04

Naming the Variables

Identify the variables related to the question. For this question, there are two variables: the color of the product and the customer's choice. These variables can be organized and compared to find any potential correlations.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Research Question Formulation
Formulating a research question is the cornerstone of any analytical task, serving as the guidepost for your investigation. It's important to devise a question that is clear, focused, and researchable. An example of a properly formulated research question is, 'Does the color of a product influence a customer's choice?'

This question is specific and measurable which makes it conducive for statistical analysis. To refine your question, consider the scope, relevance, and the potential impact of the answers obtained. Always remain open to refining your question as your understanding of the subject deepens.
Case Identification
In research, a 'case' can be an individual, group, event, or instance that is the subject of study. Identifying cases is essential as they are the basic units of analysis. In the context of our example, individual customers represent cases. Their selection provides a way to observe and measure the impact of the product's color on their choices.

To effectively identify cases, ensure they align with your research question and are accessible for observation or measurement. Consider also sample size and how representative your cases are of the wider population in order to generalize findings.
Variable Specification
Variables are the attributes that you measure, control, or manipulate in your study. Specifying your variables allows you to establish clear definitions and find the right methods to measure them. The example provided suggests two key variables: the color of the product and the customer's choice.

In variable specification, it is crucial to decide whether the variable is independent, dependent, or confounding. Here, product color is independent as it is the attribute being manipulated to observe an effect, while the choice is dependent on the color. Accurate specification of variables is critical for collecting meaningful and usable data.
Statistical Analysis
Statistical analysis is where the collected data is transformed into meaningful information. This process includes summarizing the data sets, inferring patterns, and testing hypotheses. In the context of our research question, statistical tools can calculate the correlation between product color and customer choice.

Insights such as which color is most popular or if color significantly influences choice can be revealed. When conducting statistical analysis, it's important to select the appropriate tests for your data type and research question, such as chi-square tests for categorical data or t-tests for comparing means.

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Most popular questions from this chapter

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