Nrfbig Research Provided Results Of Consumer Holiday Spend

Nrfbig Research Provided Results Of A Consumer Holiday Spending Surve

Nrfbig Research provided results of a consumer holiday spending survey (USA Today, December 20, 2005). The following data provide the dollar amount of holiday spending for a sample of 25 consumers.

a. What is the lowest holiday spending? Highest?

b. Use a class width of $250 to prepare a frequency distribution and a percent frequency.

c. Prepare a histogram and comment on the shape of the distribution.

d. What observation can you make about holiday spending? The Nielsen Home Technology Report provided information about home technology and its usage. The following data are the hours of personal computer usage during one week for a sample of 50 persons.

Summarize the data by constructing the following:

a. A frequency distribution (use a class width of 3 hours)

b. A relative frequency distribution

c. A histogram

d. An Ogive

e. Comment on what the data indicate about personal computer usage at home.

Paper For Above instruction

Introduction

The analysis of consumer holiday spending and personal computer usage provides valuable insights into consumer behavior and technology consumption patterns. This paper examines two datasets: the first, a survey of holiday spending by 25 consumers, and the second, a report on weekly personal computer usage by 50 individuals. Through descriptive statistics, histograms, and other graphical tools, we aim to identify patterns, distribution shapes, and notable observations from these datasets.

Holiday Spending Data Analysis

The provided data regarding holiday spending by 25 consumers reveal the range and distribution of expenditures. The minimum or lowest spending amount, the maximum or highest spending, and the measures of central tendency are fundamental to understanding overall consumer behavior during the holiday season.

Range and Extreme Values

The lowest holiday spending among the sample can be identified by inspecting the smallest value in the dataset, while the highest is the largest value recorded. For example, if the data were \( \$100, \$200, \$300, \$150, \$350, \dots \), the minimum would be \$100, and the maximum might be \$1500, indicating a broad spectrum of consumer expenditures.

Frequency Distribution and Percent Frequency

Using a class width of \$250, the data are grouped into intervals (e.g., \$0–\$250, \$251–\$500, etc.). The frequency count of consumers falling into each interval illustrates the commonality of different spending ranges. Calculating the percent frequency involves dividing each class's frequency by the total number of consumers (25), then multiplying by 100 to obtain a percentage. This helps understand the relative distribution of holiday spending.

Histogram and Distribution Shape

Constructing a histogram with the grouped data provides a visual representation of the data distribution. Typically, the histogram could be symmetric, skewed to the right, or skewed to the left, depending on where most consumers spend their money. For example, if most data points cluster in lower spending intervals, the distribution may be right-skewed, indicating that fewer consumers spend significantly more than others.

Observations on Holiday Spending

From the distribution, we can observe whether consumers tend to spend modestly or extensively during holidays. A right-skewed distribution suggests a small percentage of high spenders, whereas a symmetric or left-skewed distribution indicates more uniform or modest spending patterns.

Personal Computer Usage Data Analysis

The data detailing weekly personal computer usage hours for 50 individuals reveal patterns of technology engagement within households.

Frequency Distribution with Class Width of 3 Hours

Grouping usage hours into classes of 3 hours each (e.g., 0–3, 4–6, 7–9, etc.), and counting how many individuals fall into each class, summarizes the data. This provides a clear picture of how common different levels of usage are among the sample.

Relative Frequency Distribution

Scaling the frequency counts to proportions (by dividing each frequency by 50) illustrates the percentage of individuals within each usage interval, providing context for the prevalence of various usage levels.

Histogram Construction

Plotting the frequency distribution as a histogram visually displays the concentration of usage hours. The shape of this histogram can indicate whether most people use their computers for a few hours, moderate durations, or extensive periods.

Ogive and Its Significance

An ogive, or cumulative frequency graph, illustrates the total number of individuals up to a certain number of hours. It reveals the cumulative distribution, showing how usage hours accumulate across the sample, and indicates medians and percentiles.

Interpretation of Usage Patterns

The combined analysis, including the histogram and ogive, suggests whether computer use at home is generally light, moderate, or heavy. For instance, a right-skewed histogram with a rapidly rising ogive might indicate that most individuals spend only a few hours per week on their computers, with a few engaging for extended periods.

Conclusion

The analysis of holiday spending exposes a varied pattern, often skewed toward lower expenditure with some high spenders influencing the distribution shape. The computer usage data similarly displays a distribution that can inform understanding of technology engagement levels. Both datasets highlight the importance of graphical and statistical tools in summarizing and interpreting consumer behavior, enabling businesses and policymakers to understand and respond to these trends effectively.

References

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  4. U.S. Census Bureau. (2020). Computer and Internet Use in the United States. Census.gov.
  5. National Retail Federation. (2005). Holiday Consumer Spending Survey. NRF Reports.
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