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The effect of product density and ambient scent on consumer anxiety. Although retail stores overflowing with merchandise can make consumers anxious, minimally stocked spaces can have the same effect. Researchers investigated whether the use of ambient scents can reduce anxiety by creating feelings of openness in a crowded environment or coziness in a minimally stocked environment. Participants were invited to a lab that simulated a retail environment that was either jam-packed or nearly empty. For each of these two product densities, the lab was infused with one of three scents: (1) a scent associated with spaciousness such as the seashore, (2) a scent associated with an enclosed space like the smell of firewood, and (3) no scent at all. Consumers evaluated several products and their level of anxiety was measured. 28 (a) Use a diagram like Figure 92 (page 233) to display the treatments in a design with two factors: "product density" and "ambient scent." Then outline the design of a completely randomized experiment to compare these treatments. (b) There are 30 subjects avallable for the experiment, and they are to be randomly assigned to the treatments, an equal number of subjects in each treatment. Explain how you would number subjects and then randomly assign the subjects to the treatments. If you use the Simple Random Sample applet or other software, assign all the subjects. If you use Table \(B\), start at line 130 and assign subjects to only the first treatment group.

Step by step solution

01

Understand the Factors and Levels

This experiment examines two factors: 'product density' and 'ambient scent.' Product density has two levels: 'jam-packed' and 'nearly empty.' Ambient scent has three levels: 'spacious scent,' 'enclosed scent,' and 'no scent.' This creates a total of 2 (density levels) x 3 (scent levels) = 6 treatment groups.

02

Design the Diagram

To display the treatments in a figure like Figure 92, imagine a table with 'product density' as the column header (with columns 'jam-packed' and 'nearly empty') and 'ambient scent' as the row header (with rows 'spacious scent,' 'enclosed scent,' and 'no scent'). Each cell in this table corresponds to one of the six treatment groups.

03

Plan the Experiment Design

This is a completely randomized experiment. First, all 30 subjects are assigned randomly to one of the six treatment groups, ensuring equal distribution: 30 subjects ÷ 6 groups = 5 subjects per group. The assignment should ensure that each group has the same number of participants to minimize confounding variables.

04

Randomly Assign Subjects Using a Table or Software

To randomly assign subjects, number them sequentially from 01 to 30. Using a random number generator or Table B (starting at line 130), select 5 unique numbers for each treatment group, ensuring no number is repeated across groups. For example, if using Table B, continue reading across the line until assigning the first 5 unique numbers to the first group, then the next 5 for the second group, and so on.

05

Implementation of Treatments

Assign each participant to their respective group, following the randomization process. Conduct the experiment by having participants placed in their designated environment (as per the product density and scent) and measure their anxiety levels after they evaluate products.

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Key Concepts

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

random assignment

Random assignment is a fundamental aspect of experimental design. It ensures that each participant in a study has an equal chance of being placed into any treatment group. This method is crucial because it eliminates selection bias, meaning that the groups are comparable and any differences in outcomes can be attributed to the treatments rather than pre-existing differences.

In the context of this experiment, random assignment involves numbering the 30 available subjects and assigning them to six different treatment groups. By using a random number table or generator, each group receives an equal number of participants, which is five in this case. This balance is vital to maintain the integrity of the experiment, as it controls for potential confounding variables.

When implementing random assignment, integrity is key. Each assignment must be done blindly without any influence over which participant goes to which group. This ensures that the results of the study are unbiased and reliable.

treatment groups

Treatment groups are central to any controlled experiment. Each group receives a different set of conditions or 'treatments' which are designed to isolate the effect of the variables being studied. By comparing outcomes from different treatment groups, researchers can assess the impact of each specific treatment.

In this research, six treatment groups arise from the combination of two product densities and three ambient scents. The groups are:

• Jam-packed with spacious scent
• Jam-packed with enclosed scent
• Jam-packed with no scent
• Nearly empty with spacious scent
• Nearly empty with enclosed scent
• Nearly empty with no scent

These groups aid in investigating how different scent and density combinations affect consumer anxiety levels feeling within a simulated retail environment.

factorial experiment

A factorial experiment is a setup where multiple factors are tested simultaneously. This allows researchers to understand the interaction between these factors and their combined effects on the outcome.

In the study of product density and ambient scent, the factorial nature comes from the two factors being assessed: 'product density' and 'ambient scent.' Each factor has multiple levels, leading to a full cross-experiment design where all combinations are tested.

Benefits of factorial designs include:

• Efficiency in exploring multiple factors at once
• Ability to detect interactions between factors
• Richness in data collected due to multiple levels

This approach provides a comprehensive view, allowing the researchers to draw conclusions not just about individual effects but also about potential synergies between different conditions.

levels in an experiment

Levels in an experiment refer to the specific conditions or categories within a factor that are tested. Each factor can have one or more levels, and in a comprehensive study, each of these levels is paired with all other levels of other factors to test their combined effect.

In the described experiment, there are two factors: 'product density' with levels 'jam-packed' and 'nearly empty', and 'ambient scent' with levels 'spacious scent,' 'enclosed scent,' and 'no scent.'

The cross-combination of these levels results in a full factorial experiment with six different permutations, providing a clear view of how each combination influences the participant's anxiety. Testing at multiple levels helps identify which specific conditions are most effective or detrimental in impacting the outcome, such as consumer anxiety in this context.