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Magnum, LLC, is a web page design firm that has two designs for an online hardware store. To determine which is the more effective design, Magnum uses one page in the Denver area and a second page in the Miami area. For each visit, Magnum records the amount of time visiting the site and the amount spent by the visitor. (a) What is the explanatory variable in this study? Is it qualitative or quantitative? (b) What are the two response variables? For each response variable, state whether it is qualitative or quantitative. (c) Explain how confounding might be an issue with this study.

Short Answer

Expert verified
The explanatory variable is the web page design (qualitative). The response variables are the time spent (quantitative) and money spent (quantitative). Confounding can occur due to location differences influencing results.

Step by step solution

01

- Identify the explanatory variable in the study

The explanatory variable is the different web page designs used in the Denver and Miami areas. This variable is qualitative since it categorizes the pages into two distinct types.
02

- Identify the two response variables

The two response variables are the amount of time visitors spend on the site and the amount of money spent by the visitor. The amount of time is quantitative because it can be measured numerically in units of time (e.g., seconds, minutes). The amount spent is also quantitative because it can be measured in monetary units (e.g., dollars).
03

- Explain how confounding might be an issue with the study

Confounding can be an issue because the study uses different locations (Denver and Miami) for each design. Differences in visitor behavior, regional preferences, and other location-specific factors might influence the time spent and money spent on the site, rather than the web page design itself. Therefore, it might become difficult to isolate the effect of the web page design from these other factors.

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Key Concepts

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

Confounding Variables
Confounding variables are external factors that can affect the outcome of a study and make it difficult to isolate the effects of the explanatory variable. In the context of the study on the effectiveness of web page designs in Denver and Miami, confounding variables might include:
  • Regional preferences: People in Denver might have different tastes or priorities compared to those in Miami, which can affect their interaction with the website.
  • Local economic factors: Differences in the economical wellbeing in the two areas might influence spending habits.
  • Seasonal variations: If the study is conducted in different seasons, seasonal buying patterns could affect the outcomes.
These confounding factors make it hard to determine if the difference in time spent and money spent is due to the web page design or other regional differences. To minimize confounding, a better approach might include using randomized assignment of users to each web page design regardless of their location.
Quantitative Data
Quantitative data refers to numerical information that can be measured and analyzed statistically. In the study, the response variables—time spent on the site and money spent—are types of quantitative data.
  • Time Spent: This is measured in units such as seconds or minutes. As a numerical value, it can be used to calculate averages, medians, variances, etc.
  • Money Spent: This is also numerical, measured in units such as dollars. This data can also be summarized statistically to determine patterns, trends, and correlations.
Quantitative data is crucial because it allows for objective and precise analysis. To analyze it effectively, researchers often use descriptive statistics (e.g., mean, median) and inferential statistics (e.g., regression analysis) to draw conclusions from the data.
Qualitative Data
Qualitative data is non-numerical and often descriptive, capturing categories or characteristics. In the web design study, the web page design itself is qualitative.
  • Web Page Design: This is a category variable, where each design can fall into one of two groups used in Denver and Miami, without any numerical value attached.
This type of data can include text, images, or even behavior descriptions. Qualitative data is often used to explore more complex phenomena that cannot be captured by numbers alone. It can be analyzed for themes, patterns, and narratives. In the context of the study, qualitative feedback could further be collected through interviews or surveys to understand user experiences and preferences. This could provide deeper insights into the effectiveness of each design beyond just time and money spent.

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Most popular questions from this chapter

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