https://uopcourses.com/category/qnt-275/ QNT/275 STATISTICS FOR DECISION MAKING

1. QNT/275
STATISTICS FOR DECISION MAKING
The Latest Version A+ Study Guide
**********************************************
QNT 275 Entire Course Link
https://uopcourses.com/category/qnt-275/
**********************************************
QNT 275 Week 1 Practice:Connect Knowledge Check
Complete the Week 1 Knowledge Check in Connect.
Note: You have unlimited attempts available to complete practice assignments.
1.
Daily temperature in a local community collected over a 30-day time period is an example of cross-sectional
data.
True
False
2.
Time series data are data collected at the same time period.
True
False

2. 3.
Primary data are data collected by an individual.
True
False
4.
A random sample is selected so that every element in the population has the same chance of being included in
the sample.
True
False
5.
__________ consists of a set of concepts and techniques that are used to describe populations and samples.
Data mining
Traditional statistics
Random sampling
Time series analysis
6.
A sequence of operations that takes inputs and turns them into outputs is a ____________.
statistical inference
process
random sampling
runs plot
7.
Processes produce outputs over time.
True
False

3. 8.
_________ uses traditional or new er graphics to present visual summaries of business information.
Data mining
Descriptive analytics
Predictive analytics
Association learning
9.
The number of sick days taken by employees in 2008 for the top 10 technology companies is an example of
time series data.
True
False
10.
A population is a set of existing units.
True
False
11.
A(n) _____________ variable is a qualitative variable such that there is no meaningful ordering or ranking of
the categories.
interval
ordinal
ratio
nominative
12.
Judgment sampling occurs w hen a person w ho is extremely know ledgeable about the population under
consideration selects the population element(s) that they feel is(are) most representative of the population.
True
False

4. A population is a set of existing units.
True
False
Processes produce outputs overtime.
True
False
Primary data are data collected by an individual.
True
False
It is possible to use a random sample from a population to make statistical inferences about the entire
population.
True
False
The term big data was derived from the use of survey data.
True
False
_________ uses traditionalor newer graphics to present visual summaries of business information.
Predictive analytics
Data mining
Descriptive analytics
Association learning
An example of a qualitative variable is the mileage of a car.
True
False
Any characteristic of an element is called a ____________.
process
set
variable
D)census
A sequence of operations that takes inputs and turns them into outputs is a ____________.
random sampling
statistical inference
process
runs plot

5. Daily temperature in a local community collected over a 30-day time period is an example of
cross-sectionaldata.
True
False
An example of a quantitative variable is the manufacturer of a car.
True
False
Cross-sectional data are data collected at the same point in time.
True
False
QNT 275 Week 1 Apply Connect Week 1 Exercise
Review the glossary in your textbook in preparation for this assignment.
Complete the Week 1 Exercise in Connect.
Note: You have only 1 attempt available to complete assignments.
1.
Define Ratio Variable.
A variable having values that are numbers w hich reflect quantities or measurements.
A characteristic from a sample or population that can assume different values for ind ividual elements (members)
of the sample or population.
A quantitative variable such that ratios of its values are meaningful and for w hich there is an inherently defined
zero value.
Facts and figures from w hich conclusions may be draw n, generally for a specific study or issue.
2.
Define Inferential Statistics.
Efforts to mislead users of statistical information including biased sampling, misleading chart, table and
descriptive measures, and inappropriate analysis or inappropriate interpretation of the results.
The process of using a sample of measurements/values to make generalizations about the important aspects
of a population of measurements/values.

6. A sampling design in w hich w e divide a population into subgroups that do not overlap, then select a random
sample from each subgroup (stratum).
A sample selected in such a w ay that every element in the population has an equal chance of being selected.
3.
Define Variable.
A characteristic from a sample or population that can assume different values for individual elements (members)
of the sample or population.
A variable having values that indicate into w hich of several categories the value for the respective sample or
population element belongs.
Data collected over several time periods.
A variable having values that are numbers w hich reflect quantities or measurements.
4.
Define Stratified Sampling.
Efforts to mislead users of statistical information including biased sampling,
misleading chart, table and descriptive measures, and inappropriate analysis or
inappropriate interpretation of the results.
A sampling design in which we divide a population into subgroups that do not
overlap, then select a random sample from each subgroup (stratum).
A qualitative variable value for which there is no ordering or ranking; data values
are not numerical and fit into categories.
A qualitative variable value for which there is ordering or ranking.
5.
Define Sample.
The process of organizing and describing important elements of a set of values.
A sample selected in such a w ay that every element in the population has an equal chance of being selected.
The process of using a sample of measurements/values to make generalizations about the important aspects
of a population of measurements/values.
A subset of the elements in a population.
6.

7. Define Ordinal Variable.
A quantitative variable such that ratios of its values are not meaningful and for w hich there is not an inherently
defined zero value.
Facts and figures from w hich conclusions may be draw n, generally for a specific study or issue.
A quantitative variable such that ratios of its values are meaningful and for w hich there is an inherently defined
zero value.
A qualitative variable value for w hich there is ordering or ranking.
7.
Define Descriptive Statistics.
The process of using a sample of measurements/values to make generalizations
about the important aspects of a population of measurements/values.
A sampling design in which we divide a population into subgroups that do not
overlap, then select a random sample from each subgroup (stratum).
The process of organizing and describing important elements of a set of values.
A sample selected in such a way that every element in the population has an
equal chance of being selected.
8.
Define Random Sampling.
A sampling design in w hich w e divide a population into subgroups that do not overlap, then select a random
sample from each subgroup (stratum).
A sample selected in such a w ay that every element in the population has an equal chance of being selected.
A qualitative variable value for w hich there is no ordering or ranking; data values are not numerical and fit into
categories.
Efforts to mislead users of statistical information including biased sampling, misleading chart, table and
descriptive measures, and inappropriate analysis or inappropriate interpretation of the results.
9.
Define Qualitative Variable.
A variable having values that indicate into w hich of several categories the value for the respective sample or
population element belongs.
Data collected over several time periods.
The set of all elements about w hich w e w ant to draw conclusions.

8. A subset of the elements in a population.
10.
Define Interval Variable.
Facts and figures from w hich conclusions may be draw n, generally for a specific study or issue.
A quantitative variable such that ratios of its values are not meaningful and for w hich there is not an inherently
defined zero value.
A quantitative variable such that ratios of its values are meaningful and for w hich there is an inherently def ined
zero value.
A characteristic from a sample or population that can assume different values for individual elements (members)
of the sample or population.
10
Define Nominative or Nominal Variable.
A qualitative variable value for which there is ordering or ranking.
A quantitative variable such that ratios of its values are meaningful and for which there is
an inherently defined zero value.
A quantitative variable such that ratios of its values are not meaningful and for which there
is not an inherently defined zero value.
A qualitative variable value for which there is no ordering or ranking; data values are not
numerical and fit into categories.
11
Define Population.
A subset of the elements in a population.
The set of all elements about which we want to draw conclusions.
The process of organizing and describing important elements of a set of values.
The process of using a sample of measurements/values to make generalizations about
the important aspects of a population of measurements/values.
12
Define Unethical Statistical Practices.

9. A qualitative variable value for which there is ordering or ranking.
Efforts to mislead users of statistical information including biased sampling, misleading
chart, table and descriptive measures, and inappropriate analysis or inappropriate
interpretation of the results.
A qualitative variable value for which there is no ordering or ranking; data values are not
numerical and fit into categories.
A quantitative variable such that ratios of its values are not meaningful and for which there
is not an inherently defined zero value.
13
Define Quantitative Variable.
The set of all elements about which we want to draw conclusions.
Data collected over several time periods.
A variable having values that indicate into which of several categories the value for the
respective sample or population element belongs.
A variable having values that are numbers which reflect quantities or measurements.
14
Define Data Set.
Facts and figures from which conclusions may be drawn, generally for a specific study or
issue
A characteristic from a sample or population that can assume different values for
individual elements (members) of the sample or population.
A variable having values that indicate into which of several categories the value for the
respective sample or population element belongs.
A variable having values that are numbers which reflect quantities or measurements.
15
Define Time Series Data.
Data collected over several time periods.
A subset of the elements in a population.
The set of all elements about which we want to draw conclusions.
The process of organizing and describing important elements of a set of values.

10. QNT 275 Week 1 I1 Statistics in Business
Write a 300-word summary that addresses the following criteria:
 Define statistics.
 Identify different types and levels of statistics.
 Describe the role of statistics in business decision-making.
 Provide at least two examples or problem situations in which statistics was used
or could be used.
Format your summary consistent with APA guidelines.
Click the Assignment Files tab to submit your assignment.
QNT 275 Week 2 Practice:Analysis ToolPak Installation
Complete the steps indicated in the "Installing the Analysis ToolPak" video to prepare for
this week's assignment.
Take a screenshot of the Data tab showing the installed toolpak.
Click on the Assignment Files tab to submit your screenshot.
QNT 275 Week 2 Practice:Connect Knowledge Check
Complete the Week 2 Knowledge Check in Connect.
Note: You have unlimited attempts available to complete practice assignments.
1.
In a statistics class, 10 scores were randomly selected with the following results: 74, 73,
77, 77, 71, 68, 65, 77, 67, 66.
What is the IQR?
11.00
10
5.00
5.25
12.00
2.

11. A quantity that measures the variation of a population or a sample relative to its mean is
called the ____________.
range
interquartile range
standard deviation
coefficient of variation
variance
3.
An observation separated from the rest of the data is a(n) ___________.
absolute extreme
outlier
quartile
mode
4.
Quality control is an important issue at ACME Company, which manufactures light bulbs.
To test the life-hours of their light bulbs, they randomly sampled nine light bulbs and
measured how many hours they lasted: 378, 361, 350, 375, 200, 391, 375, 368, 321.
What is the mean?
375
389.9
368
346.6
200
5.
In a statistics class, 10 scores were randomly selected with the following results (mean =
71.5): 74, 73, 77, 77, 71, 68, 65, 77, 67, 66.
What is the range?
516.20
144.00
22.72

12. 4.77
12.00
6.
Which percentile describes the first quartile, Q1?
25th
100th
75th
50th
7.
Personnel managers usually want to know where a job applicant ranked in his or her
graduating class. With a grade point average of 3.83, Michelle Robinson graduated above
the 93rd percentile of her graduating class. What is the percentile rank of a student whose
GPA was the median GPA.
75th
50th
25th
93rd
10th
8.
All of the following are measures of central tendency except the ____________.
mode
range
mean
median
9.
Quality control is an important issue at ACME Company, which manufactures light bulbs.
To test the life-hours of their light bulbs, they randomly sampled nine light bulbs and
measured how many hours they lasted (mean = 346.6).

13. 378, 361, 350, 375, 200, 391, 375, 368, 321
What is the range?
58.5
191
3424.3
10,609
342.43
10.
The local amusement park was interested in the average wait time at their most popular
roller coaster at the peak park time (2 p.m.). They selected 13 patrons and had them get in
line between 2 and 3 p.m. Each was given a stopwatch to record the time they spent in
line. The times recorded were as follows (in minutes): 118, 124, 108, 116, 99, 120, 148,
118, 119, 121, 45, 130, 118.
What is the mean?
115.5
148
118
114.15
45
11.
The local amusement park was interested in the average wait time at their most popular
roller coaster at the peak park time (2 p.m.). They selected 13 patrons and had them get in
line between 2 and 3 p.m. Each was given a stopwatch to record the time they spent in
line. The times recorded were as follows (in minutes): 118, 124, 108, 116, 99, 120, 148,
118, 119, 121, 45, 130, 118.
What is the median?
118
115.5
45
114.15
148
12.

14. When establishing the classes for a frequency table, it is generally agreed that the more
classes you use the better your frequency table will be.
True
False
QNT 275 Week 2 Apply:Connect Week 2 Case
Part 1
You manage the inventory for a car dealership. Your management would like you to
review current inventory on the dealership lot.
Review the Week 2 Data Set.
Create and calculate the following in Excel®:
1. Create a Pie Chart which summarizes colors of the cars in the sample.
2. Create a Bar Chart which summarizes the frequency of the models of the cars in
the sample.
3. Create a Frequency Table for classes of MPG, including Frequency and Relative
Frequency for the cars in the sample.
o Calculate the mean Days in Inventory for the cars in the sample.
o Compare that to the median and the mode.
4. Highlight the value that would be a better representation of the "typical" price of a
car in inventory?
5. Calculate the standard deviation of the Days in Inventory for the cars in the
sample.
6. Calculate the 5 number summary for the suggested retail prices of the cars in the
sample. This consists of the 1st, 2nd, 3rd, 4th quartile and the IQR.
Note: Part 1 is not submitted. It is only to be completed in preparation for Part 2.
Part 2
Reference your Excel® spreadsheet from Part 1.
Complete the Week 2 Case in Connect.
Note: You have only 1 attempt available to complete assignments.

15. QNT 275 Week 2 Assignment Week 2
Hi Everyone,
Please answer the following questions.
 Define statistics.
 What are the differences and similarities between samples and populations?
 What are the measures of Central Tendency and what are the assumptions for
each?
 What are measures of Dispersion used for and what are the assumptions for
each?
 What are the four scales of measurement and why is it important to be able to
identify them?
 Contrast quantitative data and qualitative data.
 Provide at least two business research questions, or problem situations, in which
statistics was used or could be used.
Format: State each question followed by your answer and submit the assignment as a
Word document.
Click the Assignment Files tab to submit your assignment.
QNT 275 Week 2 I2 (Week 2) Individual Assignment:
Business Problem
I2 (Week 2) Individual Assignment: Business Problem: Prepare a paper examining a
business problem confronting your organization or an organization you know of that you
feel could be addressed through the application of the business research process.
Describe the problem. Then present the research purpose and one research question
addressing an aspect of this problem. The question must contain the variable you will
measure. Discuss the measured variable. Use the business research problem sample I2
as a guide. This paper should be between 300-600 words. Post to the individual
assignment forum. Title the document file "Business Statistics Research Problem I2".
QNT 275 Week 3 Practice:Connect Knowledge Check
1.

16. A plant manager knows that the number of boxes of supplies received weekly is normally
distributed with a mean of 200 and a standard deviation of 20. What percentage of the time will
fewer than 160 boxes of supplies arrive in a week?
2.28%
4.56%
42.07%
57.93%
2.
The z value tells us the number of standard deviations that a value x is from the mean.
True
False
3.
An event is a collection of sample space outcomes.
True
False
4.
Determine whether these two events are mutually exclusive: consumer with an unlisted phone
number and a consumer who does not drive.
not mutually exclusive
mutually exclusive
5.
Determine whether these two events are mutually exclusive: unmarried person and a person with
an employed spouse.
not mutually exclusive
mutually exclusive
6.
Which of the following statements about the binomial distribution is not correct?
Each trial results in a success or failure.
Trials are independent of each other.
The experiment consists of n identical trials.
The random variable of interest is continuous.
The probability of success remains constant from trialto trial.

17. 7.
For a continuous random variable x, the height of the probability curve f(x) at a particular point
indicates the value of the probability for that value.
True
False
8.
An important part of the customer service responsibilities of a cable company is the speed with
which trouble in service can be repaired. Historically, the data show that the likelihood is 0.75 that
troubles in a residential service can be repaired on the same day. For the first five troubles reported
on a given day, what is the probability that all five will be repaired on the same day?
.2373
.9990
.0010
.6328
9.
A standard normal distribution has a mean of ____________ and standard deviation of
____________.
zero, one
zero, zero
one, zero
one, one
10.
A letter is drawn from the alphabet of 26 letters. What is the probability that the letter drawn is a
vowel?
5/26
21/26
1/26
4/26
AEIOU; 5 vowels out of 26 letters.
11.
The set of all possible outcomes for an experiment is called a(n) ____________.
event
probability
sample space
experiment

18. 12.
Using the following probability distribution table of the random variable x, what is the probability
of x = 3?
5/15
2/15
1/15
3/15
QNT 275 Week 3 Assignment Week 3
Hi Everyone,
Use the data in the course materials folder to answer the following questions.
 What is the mean milk production per milk cow in California?
 What is the standard deviation of the milk production per milk cow in California?
 Why should you use the mean and standard deviation to analyze this data?
 What information does the mean and standard deviation give you?
 What is the 95% confidence interval for the mean milk production of each milk cow
in California from 1990 through 2005?
 If a milk cow in California produced a mean of 1,875 pounds of milk per month,
what percentage of production would that cow be in compared to the overall
production per milk cow in California from 1990 through 2005?
Format: State each question followed by your answer and submit the assignment as a
Word document.
Click the Assignment Files tab to submit your assignment.

19. QNT 275 I3 (Week 3) Individual Assignment: Descriptive
Statistics
I3 (Week 3) Individual Assignment: Descriptive Statistics Identify a research problem
different from the previous research problems that uses two different sets of the same
type of data. You may use any business subject. Some examples: Sales from two
different months or years. GPA's of men and women. Number of two different shelf items
sold (Coke & Pepsi) by month over a year. Home sales prices in different suburbs, cities,
counties or states. You wish to determine if there is a significant difference between the
means of the data sets. Select data that have absolute zero measurements (Ratio data).
You may use recorded data or made up data. The n sample size should be at least 10 in
each set, but not more than 29. Prepare a paper describing the research problem,
research purpose and one research question. Define the variable. Discuss the type of
data and determine the level of measurement. List the data. List alpha, the null and
alternative hypothesis, and give a brief back ground. Using either Megastats or Analysis
ToolPak do descriptive statistics on the data and do data analysis describing the data. Do
runs plot graphs. Interpret the Goodness of Fit (GOF) p-value to decide if the data is
parametric (normal) or nonparametric. Conclude. Use the sample I3 Descriptive Statistics
as a guide. This paper should be between 700-1000 words. Post as an Individual
Assignment. Title the document file "Descriptive Statistics I3".
QNT 275 Week 4 Apply:Connect Week 4 Case
Part 1
Three hundred consumers between 21 and 49 years old were randomly selected. After sampling a
new wine cooler, each was asked to rate the appeal of the phrase: "Not sweet like wine coolers,
not filling like beer, and more refreshing than wine or mixed drinks" as it relates to the new wine
cooler. The rating was made on a scale from 1 to 5, with 5 representing "extremely appealing" and
with 1 representing "not at all appealing".
As a manager overseeing the development of the concept, you bottle the wine cooler and placed it
into distribution in one test store.
Your manager has asked you to assess the data and determine the most likely customer based on
the ratings. Additionally, your manager would like you to review sales in the test store.
Use the Week 3 Data Set to create and calculate the following in Excel®
:
1. Estimate the probability that a randomly selected 21 to 49 year old consumer:
o Would give the phrase a rating of 5
o Would give the phrase a rating of 3 or higher
o Is in the 21-24 age group
o Is a male who gives the phrase a rating of 4
o Is a 35 to 49 year old who gives the phrase a rating of 1

20. o Based on the probabilities for the ratings of 4 and 5, which age/gender
demographic would be the best target audience for the new concept?
2. Create a probability distribution using the data which shows how many cartons of the
wine cooler were bought per customer in a month.
o Calculate the mean and the standard deviation of your probability distribution.
o Calculate the probability that exactly 3 six packs will be bought in a month.
o Calculate the probability that between 4 and 8 six packs will be bought in a
month.
o Calculate the probability that at least 5 six packs will be bought in a month.
o Calculate the probability that no more than 5 six packs will be bought in a
month.
3. Create a relative frequency distribution based on the wine cooler drinking temperatures.
o Create 6 bins with the same interval in each.
o Create a histogram
4. Considering the mean and standard deviation for the ideal drinking temperature:
o Calculate z values then refer to Table 6.1 - Cumulative Areas Under the Standard
Normal Curve
o Calculate the probability of the wine cooler being less than 45 degrees.
o Calculate the probability of the wine cooler being greater than 60 degrees.
o Calculate the percentage of wine coolers served at the ideal temperature, between
49 and 55 degrees.
Part 2
Reference your Excel® spreadsheet from Part 1.
Complete the Week 3 Case in Connect.
Note: You have only 1 attempt available to complete assignments.
Part 1
You manage Human Relations for your company. One of your sales managers
has retired, leaving an opening. You are considering two different
employees for the position. Both are highly qualified so you have decided
to evaluate their sales performance for the past year.
Use the Week 4 Data Set to create and calculate the following in
Excel®:
1. Determine the rangeof values in which you would expect to find the averageweekly sales for the
entire sales force in your company 90% of the time.
 Calculate the impact of increasing the confidence level to 95%?
 Calculate the impact of increasing the sample size to 150, assuming the same mean and standard
deviation, but allowing the confidence level to remain at 90%?
2. Based on the calculated confidence interval for weekly sales on the sample of 50 reps at a 90%
confidence level:

21.  Calculate both Reps’ averageweekly performance and highlight if it is greater than the
population mean.
3. You want to determine whether there is a statistically different averageweekly sales between
Sales Rep A and Sales Rep B.
 CreateNull and Alternative Hypothesis statements that would allow you to determine whether
their sales performance is statistically different or not.
 Use a significance level of .05 to conduct a t-test of independent samples to compare the average
weekly sales of the two candidates.
 Calculate the p-value?
4. Considering that individual you did not promote:
 Determine whether this person’s averageweekly sales are greater thanthe averageweekly sales
for the 50 sales reps whose data you used to develop confidence intervals.
 CreateNull and Alternative Hypothesis statements that would allow you to determine whether
the new Sales Manager’sweekly averagesales are greater thanthe sample of Sales Reps.
 Use a significance level of .05 to conduct a t-test of independent samples to compare the average
weekly sales of both.
 Calculate the p-value?
SAMPLE OF WEEKLY SALES
Sales Rep # AverageWeekly
Sales($)
Week # Weekly
Sales($) – Rep
A
Weekly
Sales($) – Rep
B
1 1228 1 4657 5839
2 7374 2 6133 2602
3 1055 3 3438 2830
4 1859 4 7394 4763
5 3938 5 4327 3740
6 1692 6 2552 1315
7 569 7 7063 1599
8 4059 8 7844 1629
9 3689 9 6898 2416
10 607 10 4003 2107
11 1370 11 6884 4237

22. 12 3735 12 4007 6322
13 3305 13 7214 2710
14 7228 14 2358 5890
15 6279 15 7745 5119
16 1671 16 1337 5184
17 5708 17 1052 3439
18 2569 18 6056 4828
19 4163 19 1495 3667
20 1519 20 3530 2518
21 7734 21 4749 6073
22 784 22 3833 5566
23 6766 23 7869 4555
24 7261 24 4541 5867
25 5034 25 6882 6039
26 7115 26 3868 1032
27 6291 27 5934 4834
28 6287 28 4447 3687
29 2080 29 5504 2214
30 7621 30 5554 4659
31 1047
32 6517
33 5172
34 3876

23. 35 5429
36 4538
37 3786
38 2510
39 4863
40 7246
41 1175
42 641
43 4269
44 7034
45 3406
46 2256
47 3182
48 5178
49 4428
50 1189
QNT 275 Week 4 Practice Connect Knowledge Check
Based on a random sample of 25 units of product X, the average weight is 102 lb and the
sample standard deviation is 10 lb. We would like to decide if there is enough evidence to
establish that the average weight for the population of product X is greater than 100 lb.
Therefore, the alternative hypothesis can be written as HA: μ > 100. (Assume the population
is normally distributed.)
True
False

24. The null hypothesis is a statement that will be accepted only if there is convincing sample
evidence that it is true.
True
False
A research study investigated differences between male and female students. Based on the
study results, we can assume the population mean and standard deviation for the GPA of
male students are µ = 3.5 and σ = 0.5. Suppose a random sample of 100 male students is
selected and the GPA for each student is calculated. What is
7.0
3.5
0.05
0.5
If we have a sample size of 100 and the estimate of the population proportion is .10, we can
estimate the sampling distribution of with a normal distribution.
True
False
The power of a statistical test is the probability of rejecting the null hypothesis when it is
false.
True
False
A recent study conducted by the state government attempts to determine whether the voting
public supports a further increase in cigarette taxes. The opinion poll recently sampled 1,500
voting age citizens. 1,020 of the sampled citizens were in favor of an increase in cigarette
taxes. The state government would like to decide if there is enough evidence to establish
whether the proportion of citizens supporting an increase in cigarette taxes is significantly
greater than .66. What is the alternative hypothesis?
p ≤ .66
p < .66
p = .66
p > .66
The t distribution always has n degrees of freedom.
True
False
It has been reported that the average time to download the home page from a government
website was 0.9 seconds. Suppose that the download times were normally distributed with a

25. standard deviation of 0.3 seconds. If random samples of 23 download times are selected,
describe the shape of the sampling distribution and how it was determined.
skewed; the original population is not a normal distribution
cannot be determined with the information that is given
normal; the original population is normal
normal; size of sample meets the Central Limit Theorem requirement
A recent study conducted by the state government attempts to determine whether the voting
public supports a further increase in cigarette taxes. The opinion poll recently sampled 1,500
voting age citizens. 1,020 of the sampled citizens were in favor of an increase in cigarette
taxes. The state government would like to decide if there is enough evidence to establish
whether the proportion of citizens supporting an increase in cigarette taxes is significantly
greater than .66. Identify the null hypothesis.
p > .66
p ≠ .66
p ≤ .66
In the upcoming election for governor, the most recent poll, based on 900 respondents,
predicts that the incumbent will be reelected with 55 percent of the votes. From the 900
respondents, howmany indicated that they would not vote for the current governor or
indicated that they were undecided?
405
400
450
495
It has been reported that the average time to download the home page from a government
website was 0.9 seconds. Suppose that the download times were normally distributed with a
standard deviation of 0.3 seconds. If random samples of 36 download times are selected,
calculate the mean of the sampling distribution of the sampling mean.
0.3
0.05
0.15
0.9
For a given hypothesis test, if we do not reject H0, and H0 is true,
no error has been committed.
a Type I error has been committed.
a Type II error has been committed.
a Type III error has been committed.

26. According to the Central Limit Theorem, if a sample size is at least _____, then for most
sampled populations, we can conclude that the sample means are approximately normal.
50
25
20
30
If the sampled population distribution is skewed, then in most cases the sampling
distribution of the mean can be approximated by the normal distribution if the sample
size n is at least 30.
True
False
The sampling distribution of a sample statistic is the probability distribution of the
population of all possible values of the sample statistic.
True
False
A(n) _____________ hypothesis is the statement that is being tested. It usually represents the
status quo, and it is not rejected unless there is convincing sample evidence that it is false.
true
research
alternative
null
The diameter of small Nerf balls manufactured overseas is expected to be approximately
normally distributed with a mean of 5.2 inches and a standard deviation of .08 inches.
Suppose a random sample of 20 balls is selected. Calculate the mean of the sampling
distribution of the sample mean.
0.8
5.2
0.08
0.018
If a population distribution is known to be normal, then it follows that
None of the other choices is correct.
the sample mean must equal the population mean.
the sample mean must equal the population mean, the sample mean must equal the
population mean for large samples, and the sample standard deviation must equal the
population standard deviation.

27. the sample standard deviation must equal the population standard deviation.
the sample mean must equal the population mean for large samples.
If p = .8 and n = 50, then we can conclude that the sampling distribution of is
approximately a normal distribution.
True
False
As the sample size increases, the standard deviation of the sampling distribution increases.
True
False
QNT 275 I4 (Week 4) Individual Assignment: t-test
I4 (Week 4) Individual Assignment: t-test Identify a research problem different from the
previous research problems that uses two different sets of the same type of data. You may
use any business subject. Some examples: Sales from two different months or years.
GPA's of men and women. Number of two different shelf items sold (Coke & Pepsi) by
month over a year. Home sales prices in different suburbs, cities, counties or states. You
wish to determine if there is a significant difference between the means of the data sets.
Select data that have absolute zero measurements (Ratio data). You may use recorded
data or made up data. The n sample size should be at least 10 in each set, but not more
than 29. Prepare a paper with a table of contents. Describe the research problem,
research purpose and one research question. Define the variable. Discuss the type of
data and determine the level of measurement. List the data. List alpha, the null and
alternative hypothesis, and give a brief back ground. Using either Megastats or Analysis
ToolPak do descriptive statistics on the data and do data analysis describing the data. Do
runs plot graphs. Interpret the Goodness of Fit (GOF) p-value to decide if the data is
parametric (normal) or nonparametric. t-test: Open Excel, log in both data sets. Go to Add
Ins, or Analysis ToolPak, Hypothesis Tests, Compare Two Independent Groups,
(Assuming Equal Variances) left mouse click highlight Group 1 then Group 2, OK.
Conclude. Use the I4 sample as a guide. This paper should be between 900-1200 words.
Post as an Individual assignment. Title the document file "t-test I4".
QNT 275 Week 5 Practice Connect Knowledge Check
A sequence of values of some variable or composite of variables taken at
successive, uninterrupted time periods is called a

28. seasonal factor.
cyclical component.
moving average.
least squares (linear) trend line.
time series.
The chi-square goodness-of-fit is _________ a one-tailed test with the
rejection region in the right tail.
never
sometimes
always
When the moving average method is used to estimate the seasonal factors
with quarterly sales data, a ______period moving average is used.
4
8
5
2
3
An experiment consists of 400 observations and four mutually exclusive

29. groups. If the probability of a randomly selected item being classified into
any of the four groups is equal, then the expected number of items that
will be classified into group 1 is _____.
100
125
150
25
The range for r2 is between 0 and 1, and the range for r is between
____________.
There is no limit for r.
−1 and 0
0 and 1
−1 and 1
In simple regression analysis, the quantity that gives the amount by which
Y (dependent variable) changes for a unit change in X (independent
variable) is called the
correlation coefficient.
coefficient of determination.
slope of the regression line.
standard error.

30. y-intercept of the regression line.
The chi-square goodness-of-fit test will be valid if the average of the
expected cell frequencies is ______________.
between 0 and 5
less than 5
at least 5
greater than 0
at least 1
Suppose that the unadjusted seasonal factor for the month of April is 1.10.
The sum of the 12 months' unadjusted seasonal factor values is 12.18.
The normalized (adjusted) seasonal factor value forApril
cannot be determined with the information provided.
is equal to 1.1.
is larger than 1.1.
is smaller than 1.1.
One use of the chi-square goodness-of-fit test is to determine if specified
multinomial probabilities in the null hypothesis are correct.
True
False

31. The slope of the simple linear regression equation represents the average
change in the value of the dependent variable per unit change in the
independent variable (X).
True
False
The upward or downward movement that characterizes a time series over
a period of time is referred to as _____________.
irregular variation
seasonal variation
a trend
cyclical variation
A major drawback of the aggregate price index is that
it is difficult to compute.
percentage comparisons cannot be made to the base year.
it does not take into account the fact that some items in the market basket
are purchased more frequently than others.
it is computed by using the values from a single time series or based on a
single product.

32. The correlation coefficient may assume any value between
0 and 1.
0 and 8.
−1 and 1.
−1 and 0.
−∞ and ∞.
The number of degrees of freedom associated with a chi-square test for
independence based upon a contingency table with 4 rows and 3 columns
is _____.
5
7
12
6
In simple linear regression analysis, we assume that the variance of the
independent variable (X) is equal to the variance of the dependent
variable (Y).
True
False
hose fluctuations that are associated with climate, holidays, and related

33. activities are referred to as __________variations.
trend
cyclical
seasonal
irregular
A ______________________ measures the strength of the relationship
between a dependent variable (Y) and an independent variable (X).
coefficient of determination
standard error
slope
correlation coefficient
When we carry out a chi-square test of independence, the chi-square
statistic is based on (r × c) − 1 degrees of freedom, where r and c denote,
respectively, the number of rows and columns in the contingency table.
True
False
The correlation coefficient is the ratio of explained variation to total
variation.
True
False

34. A multinomial probability distribution describes data that are classified
into two or more categories when a multinomial experiment is carried
out.
True
False
The ____________________ is the proportion of the total variation in the
dependent variable explained by the regression model.
correlation coefficient
slope
coefficient of determination
standard error
QNT 275 Week 5 Apply Connect Week 5 Case
You are the manager of a retail store. You want to investigate how metrics can improve the way you
manage your business.
Use the Week 5 Data Set to create and calculate the following in Excel®:
1. Conduct a goodness offit analysis which assesses orders ofa specific item by size (expected)
and items you received by size (observed).
o Conduct a hypothesis test with the objective of determining if there is a difference
between what you ordered and what you received at the .05 level of significance.
o Identify the null and alternative hypotheses.

35. o What is your conclusion?
2. Generate a scatterplot, the correlation coefficient, and the linear equation that evaluates
whether a relationship exists between the number of times a customer visited the store in the
past 6 months and the total amount of money the customer spent.
o Set up a hypothesis test to evaluate the strength ofthe relationship between the two
variables.
o Use a level of significance of .05.
3. Use the regression line formula to forecast how much a customer might spend on merchandise if
that customer visited the store 13 times in a 6 month period.
4. Consider the average monthly sales of 2014, $1310, as your base then
o Calculate indices for each month for the next two years (based on the 24 months of
data).
o Graph a time series plot.
5. In the Data Analysis Toolpak, use Excel's Exponential Smoothing option.
o Apply a damping factor of .5, to your monthly sales data, then create a new time
series graph that compares the original and the revised monthly sales data.
ORDERS VS. SHIPMENTS
Size # Ordered # Received
Extra Small 30 23
Small 50 54
Medium 85 92
Large 95 91
Extra Large 60 63
2X Large 45 42
CUSTOMERS IN PAST 6 MONTHS
Customer # # Visits $ Purchases
1 8 468
2 6 384
3 8 463
4 2 189
5 10 542
6 4 299
7 6 345
8 2 197
9 4 293
10 1 119
11 3 211
12 9 479
13 7 430
14 7 404
15 6 359
16 10 544

36. 17 9 522
18 5 327
19 6 353
20 7 405
21 4 289
22 7 386
23 7 403
24 1 146
25 7 416
26 9 485
27 3 333
28 7 241
29 2 391
30 6 268
MONTHLY SALES ($)
Month $ Sales
Jan 1375
Feb 1319
Mar 1222
Apr 1328
May 1493
Jun 1492
Jul 1489
Aug 1354
Sep 1530
Oct 1483
Nov 1450
Dec 1495
Jan 1545
Feb 1454
Mar 1322
Apr 1492
May 1678
Jun 1645
Jul 1580
Aug 1493
Sep 1719
Oct 1573
Nov 1629
Dec 1680