According to data from the city of Toronto, Ontario, Canada, there were nearly 112,000 parking infractions in the city for December 2020, with fines totaling over 5,500,000 Canadian dollars. The fines (in Canadian dollars) for a random sample of 105 parking infractions in Toronto, Ontario, Canada, for December 2020 are listed below. (Source: City of Toronto)

In Exercises 1–5, use technology. If possible, print your results.

Find the sample mean of the data.

검증된 단계별 안내

Step 1: Understand the problem. The goal is to calculate the sample mean of the fines listed in the dataset. The sample mean is the average of all the values in the dataset.

Step 2: Organize the data. The fines are listed in the images provided. Combine all the values into a single list for calculation purposes.

Step 3: Use the formula for the sample mean: \( \text{Sample Mean} = \frac{\sum x_i}{n} \), where \( x_i \) represents each individual fine and \( n \) is the total number of fines in the sample.

Step 4: Add all the fines together to calculate \( \sum x_i \). This involves summing up all the values provided in the dataset.

Step 5: Divide the total sum of fines (\( \sum x_i \)) by the total number of fines (\( n = 105 \)) to compute the sample mean.

비슷한 문제에 대한 검증된 영상 답변:

이 영상 해법은 위 문제에 도움이 된다고 튜터들이 추천한 것입니다.

영상 길이:

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주요 개념

질문에 올바르게 답하기 위해 반드시 이해해야 하는 핵심 개념들은 다음과 같습니다.

Sample Mean

The sample mean is the average of a set of values obtained from a sample of a population. It is calculated by summing all the values in the sample and dividing by the number of observations. The sample mean provides a measure of central tendency, helping to summarize the data and understand its overall behavior.

Descriptive Statistics

Descriptive statistics are methods for summarizing and organizing data to provide a clear overview of its main features. This includes measures such as mean, median, mode, and standard deviation, which help to describe the data's distribution and variability. Descriptive statistics are essential for interpreting data before conducting further analysis.

Data Visualization

Data visualization involves representing data graphically to identify patterns, trends, and insights more easily. Techniques such as charts, graphs, and tables help convey complex information in a more digestible format. In the context of the parking fines data, visualizing the distribution of fines can enhance understanding and facilitate comparisons.