Math 1 Statistics Review

The following boxplot shows the heights of students in Kyra’s Health class. Which measures of center spread should be used to describe it?

• Mean and Standard Deviation because the shape of the data is normal.

• Median and Standard Deviation because the shape of the data is skewed.

• Mean and IQR because the shape of the data is normal.

• Median and IQR because the shape of the data is skewed.

In the data set shown, how would adding a 200 change the mean and median?

14, 15, 16, 17, 18, 19

• The mean would increase a lot, the median would increase only a little.

• The mean and median would both increase a lot.

• The median would increase a lot, the mean would increase only a little.

• The mean and median would stay the same.

Ms. Michaelson drew a box and whisker plot to represent her students’ scores on a recent math test.

If Jennifer scored an 86 on her test, how does she compare to the rest of the students in her class?

• Jennifer scored in the top 25% of her class.

• here is no way of knowing how Jennifer did compared to the rest of her class.

• There were not a lot of students who scored between 85 and 95 because the whisker on the higher end of the data is shorter.

The boxplots below show test scores from Mr. Payne’s 1^st and 2^nd period classes.

Which class typically performed better?

• First period

• Second period

The data below represent the number of absences and the final grade of 9 randomly selected students from a Math 1 class. The data shows what type of correlation?

• Negative Correlation

• Positive Correlation

Tags

CCSS.HSF-LE.A.1B

The data below represent the number of absences and the final grade of 9 randomly selected students from a Math 1 class. Find the equation for the line of best fit.

• $y=-2.95x+96.12$

• $y=96.12x-2.95$

• $y=1x+1$

Tags

CCSS.8.EE.C.8C

The data below represent the number of absences and the final grade of 9 randomly selected students from a Math 1 class. The correlation coefficient for this data is -.94. What does this tell you?

• There is a strong negative correlation.

• There is a strong positive correlation.

• There is a weak negative correlation.

• There is a weak positive correlation.

The data below represent the number of absences and the final grade of 9 randomly selected students from a Math 1 class.

You are asked to predict the final grade for a student with 20 absences. This prediction is an example of...

• Interpolation

• Extrapolation

The data below represent the number of absences and the final grade of 9 randomly selected students from a Math 1 class. Predict the final grade for a student who has 20 absences.

The graph shown is the residual plot for the Number of Absences vs. Final Grade data. What does this tell you?

• There is no pattern, so a linear model is appropriate.

• There is no correlation.

• There is no pattern, so a linear model is not appropriate.

• Something is wrong here... I thought you couldn't have a negative grade! Oh boy.. I'm in trouble!