Join IDNLearn.com and start getting the answers you've been searching for. Get timely and accurate answers to your questions from our dedicated community of experts who are here to help you.

The number of cars sold at a dealership over several weeks is given below:
[tex]\[14, 23, 31, 29, 33\][/tex]

What is the standard deviation for this set of population data?

Standard deviation: [tex]\[\sigma=\sqrt{\frac{(x_1-\mu)^2+(x_2-\mu)^2+\ldots+(x_N-\mu)^2}{N}}\][/tex]

A. 6.9
B. 12.4
C. 15.4
D. 47.2


Sagot :

To find the standard deviation of the number of cars sold at a dealership over several weeks, follow these steps:

1. List the Data Points:
The number of cars sold each week is: [tex]\(14, 23, 31, 29, 33\)[/tex].

2. Calculate the Mean (μ):
Mean (μ) is found by summing all the data points and dividing by the number of data points.
[tex]\[ \mu = \frac{14 + 23 + 31 + 29 + 33}{5} = \frac{130}{5} = 26 \][/tex]

3. Calculate the Squared Differences from the Mean:
For each data point, subtract the mean and square the result.
[tex]\[ (14 - 26)^2 = (-12)^2 = 144 \][/tex]
[tex]\[ (23 - 26)^2 = (-3)^2 = 9 \][/tex]
[tex]\[ (31 - 26)^2 = 5^2 = 25 \][/tex]
[tex]\[ (29 - 26)^2 = 3^2 = 9 \][/tex]
[tex]\[ (33 - 26)^2 = 7^2 = 49 \][/tex]
These squared differences are: [tex]\(144, 9, 25, 9, 49\)[/tex].

4. Calculate the Variance (σ²):
Variance is the average of these squared differences.
[tex]\[ \sigma^2 = \frac{144 + 9 + 25 + 9 + 49}{5} = \frac{236}{5} = 47.2 \][/tex]

5. Calculate the Standard Deviation (σ):
The standard deviation is the square root of the variance.
[tex]\[ \sigma = \sqrt{47.2} \approx 6.8702 \][/tex]

Thus, the standard deviation of the number of cars sold is approximately [tex]\(6.87\)[/tex].

Reviewing the options given:

- 6.9
- 12.4
- 15.4
- 47.2

The closest option to our calculated standard deviation is 6.9.

Therefore, the correct answer is 6.9.