Bio Pro Data complete solutions correct answers key

Bio Pro Data complete solutions correct answers key

From the histogram or ogive of the variable "Pay", the percentage of the sample paid more than $40000 is:

92.97%

22.68%

7.03%

0.96%

QUESTION 2

Which of the following chart types would be best to illustrate the frequency distribution of the variable "Grade"?

Scatter plot

Pie chart

Line graph

Histogram

Bar chart

QUESTION 3

Which of the following variables is an example of nominal data:

Age

Pay

Experience

Tenure

Gender

QUESTION 4

Assuming the variable PAY is normally distributed, then.....

The mode should provide the best estimate of central tendency

The mean and the median will be about the same

The geometric mean should be used.

You should see excess kurtosis

QUESTION 5

Which of the following is an appropriate measure of variability for the variable Age:

Standard Deviation

25^th and 75^th percentile

Interquartile Range

Range

All of the above

QUESTION 6

The skewness of the variable Tenure is:

0.17

0.29

0.33

1.35

3.06

QUESTION 7

The kurtosis of the variable Education is:

5.03

2.03

1.46

1.19

-0.58

QUESTION 8

Using the mean and the standard deviation for the variable AGE, approximately what value would lie three standard deviations to the right of the mean and therefore be considered an "outlier"?

32

123

76

65

QUESTION 9

Based on the Empirical Rule, what proportion of a normally distributed sample lies above two standard deviations of the mean?

2.5%

95.0%

3.8%

45%

QUESTION 10

For a population comprising 30% males, what is the probabilility of drawing a random sample of 313 and getting 94 or fewer males? Hint: use the binomial distribution.

4.9%

30.0%

46.7%

50.0%

53.3%

QUESTION 11

If the variable "Education" were uniformly distributed over the range measured in the sample, the mean would be:

12

13

16

20

Cannot be calculated

QUESTION 12

Assume that Pay follows a normal distribution with the parameters measured by the sample. Using this information, what proportion of the population earns more than $65000?

<0.1%

2.0%

2.6%

97.4%

98.0%

QUESTION 13

Assume that Pay follows a normal distribution with the parameters measured by the sample. Using this information, what proportion of the population earns between $45000 and $55000?

20.9%

48.6%

52.4%

73.3%

Cannot be calculated

QUESTION 14

The lower bound of the 95% confidence interval for the mean of the variable "Pay" is:

$49632

$49878

$50004

$51307

$51432

QUESTION 15

The upper limit of the 95% confidence interval for the proportion of males in the sample is:

23.4%

25.0%

25.8%

35.1%

36.7%

QUESTION 16

In order test whether the mean Tenure is more than 5 years, the hypotheses should be set up as follows:

H­­­0­: µ≥5 and HA: µ≤5

H­­­0­: µ≠5 and HA: µ

H­­­0­: µ and HA: µ≠5

H­­­0­: µ≥5 and HA: µ<5

H­­­0­: µ≤5 and HA: µ>5

QUESTION 17

For the equivalent group of employees at Ellion, the mean gross annual remuneration is $51500 with a standard deviation of $7000. At a 1% significance level, testing the hypothesis that the results from the BizPro sammmple are the same results in the following decision:

Reject H­­­0

Reject HA

Accept H­­­0

Do not reject H­­­0

Do not reject HA

QUESTION 18

When testing the hypothess that the proportion of males in the sample is 35% at a 10% significance level, the decision is:

Do not reject the null hypothesis

Do not reject the alternative hypothesis

Reject the alternative hypothesis

Accept the null hypothesis

Reject the null hypothesis

QUESTION 19

The correlation between Education and Pay indicates that:

As Education increases, Pay decreases

As Education increases, Pay increases

As Education decreases, Pay increases

Pay causes Education

Education causes Pay

QUESTION 20

At a 5% significance level:

Pay and Education are correlated

Pay and Tenure are correlated

Pay and Experience are correlated

Education and Tenure are correlated

None of the above

QUESTION 21

The regression equation between Pay (dependent variable) and Education (independent variable) accounts for:

81.9% of the variance in Pay

81.4% of the variance in Pay

43.4% of the variance in Pay

18.9% of the variance in Pay

QUESTION 22

The regression equation between Pay (dependnet variable) and Education (independent variable) may be written as follows"

Pay = 2786 + 206*Education

Pay = 27138 + 1753*Education

Pay = 206 + 27138*Pay

Pay = 206 + 2786*Education

Education = 2713 + 1753*Pay

QUESTION 23

The regression equation between Pay (dependnet variable) and Education (independent variable)

An extra year of education results in an increase in Pay of $27138

An extra year of education results in an increase in Pay of $2786

An extra year of education results in an increase in Pay of $1753

An extra year of education results in an increase in Pay of $206

This cannot be determined from the regression equation