# mx sb1 5.3 Statistics ❋ Name:

Temp (°C)
26
30
46
45
88
48
41
22
22

The data provided in the table are the temperatures reported by sensors in a desktop computer. These temperatures must be within certain ranges for the computer to operate properly and not fail prematurely.

1. _________ What level of measurement is the data?
2. __________ Calculate the sample size n for the data.
3. __________ Determine the minimum.
4. __________ Determine the maximum.
5. __________ Calculate the range.
6. __________ Calculate the midrange.
7. __________ Determine the mode.
8. __________ Determine the median.
9. __________ Calculate the sample mean x.
10. 20.5149 Freebie: This is the standard deviation sx to four decimal places. If you obtain a different value, then you typed in the wrong data! Calculate the standard deviation sx and check for agreement.
11. __________ Calculate the sample coefficient of variation CV.
12. __________ If this data were to be divided into six classes, what would be the width of a single class?
13. Determine the frequency and calculate the relative frequency using six classes. Record your results in the table provided.
Temp CUL (cm)Frequency (f)Relative Frequency
Sum:
14. Sketch a frequency histogram chart of the data anywhere it fits, labeling your horizontal axis and vertical axis as appropriate.
15. ____________________ What is the shape of the distribution?
16. __________ Use the sample mean x and standard deviation sx calculated above to determine the z-score for 88 °C.
17. ____________________ Is the z-score for 88 °C an ordinary or unusual z-score?
18. p(T < 33 °C) = __________ What is the probability that a system temperature T will be below 33°C?

```y = 1.09306x + 24.703
```

The table provides running time versus temperature data for a computer.

1. _________ Calculate the sample size n.
2. _________ Calculate the slope of the linear regression.
3. _________ Calculate the y-intercept of the linear regression.
4. _________ Is the relation between Run Time (hrs) and Temp (°C) positive, negative, or neutral?
5. _________ Calculate the correlation coefficient r for the data.
6. ______________ Is the correlation none, weak/low, moderate, strong/high, or perfect?
7. ______________ Determine the coefficient of determination.
8. ______________ What percent in the variation in Run Time (hrs) "explains" the variation in Temp (°C)?
9. _________ Use the slope and intercept to predict the CPU Temp (°C) for a Run Time (hrs) equal to 7 hrs.
10. _________ Use the slope and intercept to determine the Run Time (hrs) at which the Temp (°C) is predicted to be 30 °C.
```14sample size n  5
15slope  1.09
16intercept  24.7
17nature positive
18correlation 0.9
19strength strong
20coef det  0.810
21perc variation81.00%
227 hrs.32.35 Temp (°C)
2330 °C.4.85 Run Time (hrs)
ttest:  3.5759
p-value:  0.0373946
max c 0.9626054
```