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using the given calculator, find the iqr, standard deviation, and any o…

Question

using the given calculator, find the iqr, standard deviation, and any outliers. 52, 42, 49, 48, 34, 42, 49, 54, 41 multiple-choice question what is the standard deviation? 5.98 1.75 2.56 6.34

Explanation:

Step 1: Find the mean ($\mu$)

First, we calculate the mean of the data set. The data set is \( 52, 42, 49, 48, 34, 42, 49, 54, 41 \). The sum of the data points is:
\[
52 + 42 + 49 + 48 + 34 + 42 + 49 + 54 + 41 = 411
\]
There are \( n = 9 \) data points. So the mean is:
\[
\mu=\frac{411}{9} = 45.666\ldots\approx45.67
\]

Step 2: Calculate the squared differences from the mean

For each data point \( x \), we calculate \( (x - \mu)^2 \):

  • For \( 52 \): \( (52 - 45.67)^2=(6.33)^2 = 40.0689 \)
  • For \( 42 \): \( (42 - 45.67)^2=(- 3.67)^2 = 13.4689 \)
  • For \( 49 \): \( (49 - 45.67)^2=(3.33)^2 = 11.0889 \)
  • For \( 48 \): \( (48 - 45.67)^2=(2.33)^2 = 5.4289 \)
  • For \( 34 \): \( (34 - 45.67)^2=(-11.67)^2 = 136.1889 \)
  • For \( 42 \): \( (42 - 45.67)^2=(-3.67)^2 = 13.4689 \)
  • For \( 49 \): \( (49 - 45.67)^2=(3.33)^2 = 11.0889 \)
  • For \( 54 \): \( (54 - 45.67)^2=(8.33)^2 = 69.4089 \)
  • For \( 41 \): \( (41 - 45.67)^2=(-4.67)^2 = 21.8089 \)

Step 3: Find the sum of squared differences

Now we sum up all these squared differences:
\[

$$\begin{align*} &40.0689+13.4689 + 11.0889+5.4289+136.1889+13.4689+11.0889+69.4089+21.8089\\ =&(40.0689+13.4689)+(11.0889 + 5.4289)+(136.1889+13.4689)+(11.0889+69.4089)+21.8089\\ =&53.5378+16.5178+149.6578+80.4978+21.8089\\ =&53.5378+16.5178 = 70.0556\\ &70.0556+149.6578=219.7134\\ &219.7134 + 80.4978=300.2112\\ &300.2112+21.8089 = 322.0201 \end{align*}$$

\]

Step 4: Calculate the variance ($\sigma^2$)

The variance is the average of the squared differences. Since this is a population (we are not dealing with a sample), the variance \( \sigma^2=\frac{\sum(x - \mu)^2}{n} \)
\[
\sigma^2=\frac{322.0201}{9}\approx35.78
\]

Step 5: Calculate the standard deviation ($\sigma$)

The standard deviation is the square root of the variance:
\[
\sigma=\sqrt{35.78}\approx5.98
\]

Answer:

5.98