Question

Find the weighted mean of the data. The scores and their percents of the final grade for a statistics student are shown below. What is the student's mean score? (TABLE CAN'T COPY)

Name: Problem 41, Chapter 2: Elementary Statistics: Picturing the World
Uploaded: 2020-10-28T15:58:29-08:00
Duration: 4 min 5 s
Channel: Pammi Eswari
Description: Find the weighted mean of the data. The scores and their percents of the final grade for a statistics student are shown below. What is the student's mean score? (TABLE CAN'T COPY)

   Find the weighted mean of the data.
The scores and their percents of the final grade for a statistics student are shown below. What is the student's mean score? 
(TABLE CAN'T COPY)

Elementary Statistics: Picturing the World

Ron Larson, Betsy… 6th Edition

Chapter 2, Problem 41

Instant Answer

Solved by Expert Pammi Eswari

10/28/2020

Step 1

The score is denoted as \(X\) and the percentage as \(f\). For example, if the student scored 85 on homework and this represents 5% of the final grade, we write this as \(X = 85\) and \(f = 0.05\). The product of \(X\) and \(f\) gives us \(4.25\). Show more…

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Find the weighted mean of the data. The scores and their percents of the final grade for a statistics student are shown below. What is the student's mean score? (TABLE CAN'T COPY)

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Key Concepts

Weighted Mean

The weighted mean is a type of average where each data point contributes to the final result based on its relative importance or weight. In contrast to a simple mean, every value in the data set is multiplied by a corresponding weight, and the sum of these products is then divided by the total of the weights. This approach ensures that values with more significance have a greater impact on the average.

Weights

Weights represent the relative importance or frequency of each data point in the calculation. In many applications, including computing a final grade, weights are assigned to different scores or outcomes to reflect their contribution to the aggregate result. They allow you to combine values that might not contribute equally to the total outcome, emphasizing more significant components.

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