Chapter 1
...
In statistical analysis, inferential statistics is used to
only 1 and 2 are correct
A summary measuere computed from a population is referred to as a
Parameter
An example of a population parameter is
a and b are both parameters
From the following, identify the example of a continuous variable.
both 2 and 4 are continuous
Qualitative data
may be either numeric or nonnumeric
Which of the following is an example of a quantitative variable?
the number of students in a room
Social security numbers consist of numeric values. Therefore, social security is an example of
a qualitive variable
___________ data are not really numerical but are merely levels or categories or simply assigned values. The example would be sex (1-Male 2-Female), or directions (1-E 2-W 3-N 4-S).
nominal data
When your data is NOT a sequence of observations that taken in an orderly fashion with respect to time you are using
cross sectional data
When your data is a sequence of observations that taken in an orderly fashion with respect to time you are using
time series data
Chapter 2
...
The absolute frequency for the class 25 but < 35 is
the number of observations in the data set >= 25 but < 35
The relative frequency for the class 25 but < 35 is
the number of observations in the data set >= 25 but < 35 divided by the sample size
The cumulative relative frequency for the class 25 but < 35 is
the number of observations in the data set < 35 divided by the sample size
What is the standard class width for the following table?
Class (items/day)
20 But < 40
40 but < 50
50 but < 60
60 but < 70
70 but < 80
80 but <90
90 but <110
Total
10
The first class in the following table:
24 But <40
40 But < 44
44 but < 48
48 but < 52
52 but < 56
56 but < 60
60 but < 64
64 but < 68
68 but < 72
b and c are both correct
What is the cumulative absolute frequency for the class 80 but < 100 in the following table?
Class (production/day) Absolute Frequency
0 but < 40 5
40 but < 60 10
60 but < 80 50
80 but < 100 80
100 but < 120 35
120 but < 200 20
Total 200
145
Consider for the following table and histogram:
Class (production/day)
Absolute Frequency
0 but < 40
4
40 but < 60
8
60 but < 80
49
80 but < 100
80
100 but < 120
39
120 but < 200
20
Total
200
the histogram does NOT correctly represent the absolute frequency distribution in the table
What is Q1 given the following data:
7
3
9
5
5
5
6
6
6
2
9
4
4.5
What is Q2 given the following data:
7
3
9
5
5
5
6
6
6
2
9
4
none of the above
What is Q3 given the following data:
7
3
9
5
5
5
6
6
6
2
9
4
6.5
Chapter 3
...
When computing the mean of a data set the solution would be the same regardless of whether the data are from a population or a sample.
TRUE
The mean (called the "average" in excel) is the most widely used measure of central tendency (computer by summing the numbers in the data set and then dividing by the number of numbers) and is robust of outliers in the data set.
FALSE
What is the standard deviation of the Spring sample data set?
Spring
500
560
556
600
530
500
38.8587
What is the mean of the Spring sample data set?
Spring
500
560
556
600
530
500
541
What is the mode of the Spring sample data set?
Spring
500
560
556
600
530
500
500
Suppose you have two data sets. The first data set has a mean of 100 and a standard deviation of 10. The second data set has a mean of 500 and a standard deviation of 75. Which data set is MORE relatively dispersed according the to coefficient of variatio
The second data set is more relatively dispersed
Examine the smallest and largest Spring data values in the Spring sample data set. List any Spring data values you believe should not be in the Spring data set (values you believe to be outliers that are too small or too large).
Re-compute the mean, media
there are no outliers in the Spring data so no numbers should be removed
The standard deviation of a data set can be
zero or positive
What is the range of the Spring data set?
Spring
500
560
556
600
530
500
none of these
What is the median of the Summer sample data set?
Summer
552
550
552
546
549
548
551
1500
555
556
551.5
Chapter 4
...
What is the probability z will be greater than -2.05?
0.9798
What is the probability z will be less than -1.27?
0.102
What is the probability z will be between .25 and 1.75?
0.3612
87.49% of the area is below what value of z?
1.15
The middle .9146 area of the z distribution is between what 2 numbers?
-1.72, 1.72
The life expectancy of a particular brand of tire is normally distributed with a mean of 40,000 and a standard deviation of 5,000 miles. What is the probability that a randomly selected tire will have a life of at least 47,500 miles?
0.0668
You sell different beverages at your resturant. One of the most profitable products you sell is a customized UNCW Seahawk coffee blend. You know the number of cups sold per day is a normally distributed random variable with �x = 200 cups and ?x = 50 cups.
0.7517
The weight of soccer players is normally distributed with a mean of 200 pounds and a standard deviation of 25 pounds. The probability of a player weighing less than 180 pounds is
0.2119
You sell different beverages at your resturant. One of the most profitable products you sell is a customized UNCW Seahawk coffee blend. You know the number of cups sold per day is a normally distributed random variable with �x = 200 cups and ?x = 50 cups.
0.4993
You sell different beverages at your restaurant. One of the most profitable products you sell is a customized UNCW Seahawk coffee blend. You know the number of ounces sold per day is a normally distributed random variable with �x = 500 ounces and ?x = 75
608.75
Chapter 6
...
What is the probability z will be greater than -2.05?
0.9798
What is the probability z will be less than -1.27?
0.102
What is the probability z will be between .25 and 1.75?
0.3612
87.49% of the area is below what value of z?
1.15
The middle .9146 area of the z distribution is between what 2 numbers?
-1.72, 1.72
The life expectancy of a particular brand of tire is normally distributed with a mean of 40,000 and a standard deviation of 5,000 miles. What is the probability that a randomly selected tire will have a life of at least 47,500 miles?
0.0668
You sell different beverages at your resturant. One of the most profitable products you sell is a customized UNCW Seahawk coffee blend. You know the number of cups sold per day is a normally distributed random variable with �x = 200 cups and ?x = 50 cups.
0.7517
The weight of soccer players is normally distributed with a mean of 200 pounds and a standard deviation of 25 pounds. The probability of a player weighing less than 180 pounds is
0.2119
You sell different beverages at your resturant. One of the most profitable products you sell is a customized UNCW Seahawk coffee blend. You know the number of cups sold per day is a normally distributed random variable with �x = 200 cups and ?x = 50 cups.
0.4993
You sell different beverages at your restaurant. One of the most profitable products you sell is a customized UNCW Seahawk coffee blend. You know the number of ounces sold per day is a normally distributed random variable with �x = 500 ounces and ?x = 75
608.75
You sell different beverages at your restaurant. One of the most profitable products you sell is a customized UNCW Seahawk coffee blend. You know the number of ounces sold per day is a normally distributed random variable with �x = 500 ounces and ?x = 75
608.75
Chapter 7
...
A simple random sample of size n from an infinite population of size N is to be selected. Each possible sample should have
an equal chance of being selected
A simple random sample of 100 observations was taken from a large population. The sample mean and the standard deviation were determined to be 80 and 12 respectively. The standard error of the mean is
1.2
The sampling error is the
difference between the value of a sample mean and the value of the population mean
Random samples of size 81 are taken from an infinite population whose mean and standard deviation are 200 and 18, respectively. The distribution of the population is unknown. The mean and the standard error of the mean are
200 and 2
The sampling distribution of the sample mean, mc003-1.jpg , is
a probability distribution of all possible sample means
Whenever the population has a normal probability distribution, the sampling distribution of mc026-1.jpg is a normal probability distribution for
any sample size
Suppose the number of items you can deliver in a day is a random variable with some unknown distribution with a mean = 35 and a standard deviation of 8. What is the probability a random sample of 36 days would have a mean greater than 37.32?
0.0409
Suppose the number of items you can deliver in a day is a random variable with some unknown distribution with a mean = 35 and a standard deviation of 8. What is the probability a random sample of 36 days would have a mean between 31.8 and 37?
0.925
Suppose the number of items you can deliver in a day is a random variable with some unknown distribution with a mean = 35 and a standard deviation of 8. 98.98% of all sample means of 36 days will be less than ?.
38.0933
Suppose the number of items you can deliver in a day is a random variable with some unknown distribution with a mean = 35 and a standard deviation of 8. 98.98% of all sample means of 36 days will be greater than ?.
31.9067
&
38.0933
Chapter 8
...
A low level of confidence for a confidence interval would mean
a high chance of a type I error
A 90% confidence interval for a population mean is determined to be 100 to 130. If the confidence coefficient is increased to 0.95, the interval
would be more than 30
The purpose of constructing a confidence interval is to
estimate a population parameter with a sample statistic at some level of confidence
For a two-sided confidence interval with 18 observations, ?x known, and ? = 0.20 the (critical) value is:
1.282
For a two-sided confidence interval with 13 observations, ?x known, and ? = 0.10 the (critical) value is
1.645
For a two-sided confidence interval with 14 observations, ?x unknown, and ? = 0.10 the (critical) value is:
none of these
For a two-sided confidence interval with 15 observations, ?x unknown, and ? = 0.10 the (critical) value is:
1.761
For a two-sided confidence interval with 18 observations, ?x unknown, and ? = 0.10 the (critical) value is:
1.74
An economist is trying to determine the average per capita income (in thousands of dollars) of the residents of a major city in Texas. Suppose a sample of size 25 is drawn from the city with the following results: sample mean = 26 and sx = 9.6. Construct
22.7149
An economist is trying to determine the average per capita income (in thousands of dollars) of the residents of a major city in Texas. Suppose a sample of size 26 is drawn from the city with the following results: sample mean = 26 and sx = 9.6. Construct
28.4777
Chapter 9
...
In a hypothesis test, if you do not reject the null hypothesis at an ? of .05 you know you would have also
not rejected Ho if ? had been .025
A manufacturer of potato chips would like to know whether its bag filling machine is under-filling bags of chips at the 426 gram setting. The alternative hypothesis would be:
?x < 426
When you set the value of alpha (?) or type I error in a hypothesis test you are also setting the
1 thru 3 are all true
In a hypothesis test for the population mean, when the population standard deviation ( sigma ) is known your test statistic has a ______ distribution.
Z
For a Lower one-tailed hypothesis test with a sample size of 18 at ? = .10, the critical value for the decision would be:
none of these
The decision rule for the p-value approach is
Reject the Null hypothesis in favor of the alternative hypothesis if P-value < alpha (?).
Given the following hypothesis test:
Ho: mu of x is greater or equal to 54
Ha: mu of x is less than 54
and this information:
n = 64 , X bar = 50 , S of x = 16 , Standard deviation is unknown
The p-value is between
.02 and .025
A random sample of 16 students selected from the student body of a large university had an average age of 25 years and a standard deviation of 2 years. We want to use hypothesis testing to determine if the average age of all the students at the university
2
Suppose you are testing the alternative hypothesis, Ha: ?x ? 0 and your Decision is "Do Not Reject Ho". Your conclusion would be:
there is not sufficient evidence to conclude HA is true
Given the following hypothesis test:
Ho: mu of x is less than or equal to 20
Ha: mu of x is more than 20
and this information:
n = 36 , X bar = 24.6 , S of x = 12, Standard deviation is unknown
You decision using ? = .05 would be:
the null hypothesis should be rejected
Chapter 10
...
If you perform a hypothesis test on the population slope Parameter (?1) in regression analysis and reject the Null hypothesis: Ho: ?1= 0. Your conclusion would be:
The least squares sample regression equation should be used because there is
sufficient evidence of a relationship between the independent variable and the dependent variable..
In regression analysis the parameter ?1 is a Population Parameter measuring
the slope of the Population regression line computed from a census of the Population
In regression analysis the parameter Beta0 (?0) is a Population Parameter measuring
the Y intercept of the Population regression line computed from a census of the Population
Simple Linear Regression analysis is a statistical procedure for developing a mathematical equation that describes how
one dependent and one independent variables are related
Our company processes widgets. Consider the following data for 23 widgets. Each widget was weighed before and after processing.
Widget
Weight before processing (pounds)
Weight after processing (pounds)
1
0.1
0.07
2
0.17
0.02
3
0.4
0.16
4
0.75
0.15
5
0.66
.0114 pounds
Our company processes widgets. Consider the following data for 23 widgets. Each widget was weighed before and after processing.
Widget Weight before processing (pounds) Weight after processing (pounds)
1
0.1
0.07
2
0.17
0.02
3
0.4
0.16
4
0.75
0.15
5
0.66
.228 pounds
his following data is for Wray Enterprises. We have tracked the amount of money they spend on advertising and the sales volume for their product.
Month
Advertising
Sales
1
1000
5200
2
1500
6000
3
1900
7200
4
1400
5400
5
2200
6500
6
2468
7600
7
1210
6200
8
there is sufficient evidence of a positive relationship between advertising and sales
This following data is for Wray Enterprises. We have tracked the amount of money they spend on advertising and the sales volume for their product.
Month
Advertising
Sales
1
1000
5200
2
1500
6000
3
1900
7200
4
1400
5400
5
2200
6500
6
2468
7600
7
1210
6200
I would use the model to predict for advertising of $1500 and $2400 only.