The document discusses the topics of several weekly discussions in an analytics course. It provides questions and prompts for students to discuss topics like data analytics vs statistics, descriptive vs predictive vs prescriptive analytics, hypothesis testing, linear regression modeling, and time series analysis and decomposition. Students are asked to post initial responses of at least 175 words and reply to two other classmates.

1. DAT 565 All Discussions
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DAT 565 Wk 1 Discussion - Data Analytics and Statistics
Post a total of 3 substantive responses over 2 separate days for full participation.
This includes your initial post and 2 replies to other students or your faculty member.
Due Thursday
This week’s required readings explain the role that analytics plays in the modern business
environment. Consider the following questions and respond in a minimum of 175 words:
 How is data analytics different from statistics?
 Analytics tools fall into 3 categories:descriptive, predictive, and prescriptive. What
are the main differences among these categories?
 Explain how businesses use analytics to convert raw operational data into
actionable information. Provide at least 1 example.
 Consider the organization you work for (or another organization you’re familiar
with). Does this organization use data analytics?If so, how is it used? If not, how could the
organization use data analytics to improve its performance?
Due Monday
Reply to at least 2 of your classmates or your faculty member. Be constructive and
professional.
DAT 565 Wk 2 Discussion - Metrics and Information Visualization
Post a total of 3 substantive responses over 2 separate days for full participation.
This includes your initial post and 2 replies to other students or your faculty member.
Due Thursday

2. Respond to the following in a minimum of 175 words:
The most frequently used measures of central tendency for quantitative data are the mean
and the median. The following table shows civil service examination scores from 24
applicants to law enforcement jobs:
83 74 85 79
82 67 78 70
18 93 64 27
93 98 82 78
68 82 83 99
96 62 93 58
Using Excel, find the mean, standard deviation, and 5-number summary of this sample.
 Construct and paste a box plot depicting the 5-number summary.
 Does the dataset have outliers? If so, which one(s)?
 Would you prefer to use the mean or the medianas this dataset’s measure of
central tendency? Why?
Due Monday
Reply to at least 2 of your classmates or your faculty member. Be constructive and
professional.
For More Classes Please Visit
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DAT 565 Wk 3 Discussion - Characterizing Uncertainty
Post a total of 3 substantive responses over 2 separate days for full participation.
This includes your initial post and 2 replies to other students or your faculty member.
Due Thursday
Respond to the following discussion prompt in a minimum of 175 words:

3. Many business activities generate data that can be thought of as random. An example
described in the textbook is the servicing of cars at an oil change shop. Each car entering
the shop can be considered an experiment with random outcomes. A variable of interest
in this experiment could be the amount of time necessary to service the car. Service time
will vary randomly with each car.
We can often capture the most relevant characteristics of a stochastic process with a
simple probability distribution model. We can then analyze the model to make predictions
and drive decisions. For instance, we could estimate the number of technicians the oil
change shop needs to service demand on a Saturday afternoon. Discuss the following:
 What is a random variable?
 How would you differentiate a discrete from a continuous random variable?
A laptop manufacturing company has implemented a 2-step process to test the quality of
each production batch. In the first step, a technician randomly selects 15 laptops from the
batch and determines whether they meet specifications. The batch is considered
acceptable provided no more than 1 laptop fails to meet specifications. Otherwise, the
entire batch must be tested in the second step. Historical data shows that 95% of the
laptops produced adhere to specifications. Discuss the following:
 What are the 4 characteristics of a binomial experiment?
 Can we use a binomial distribution to model this process?
 What is the probability that the entire batch unnecessarily has to be tested if in fact
95% of its laptops conform to specifications? (Hint: Use Excel’s =BINOMDIST() function to
find the probability.)
 What is the probability that the batch is incorrectly accepted if only 75% of its
laptops conform to specifications?
Due Monday
Reply to at least 2 of your classmates or your faculty member. Be constructive and
professional.
For More Classes Please Visit
http://www.uopstudy.com/
DAT 565 Wk 4 Discussion - Testing Hypotheses
Post a total of 3 substantive responses over 2 separate days for full participation.
This includes your initial post and 2 replies to other students or your faculty member.

4. Due Thursday
Hypothesis testing is used in business to test assumptions and theories. These
assumptions are tested against evidence provided by actual, observed data. A statistical
hypothesis is a statement about the value of a population parameter that we are
interested in. Hypothesis testing is a process followed to arrive at a decision between 2
competing, mutually exclusive, collective exhaustive statements about the parameter’s
value.
Consider the following scenario: An industrial seller of grass seeds packages its product in
50-pound bags. A customer has recently filed a complained alleging that the bags are
underfilled. A production manager randomly samples a batch and measures the following
weights:
Weight, (lbs)
45.6 49.5
47.7 46.7
47.6 48.8
50.5 48.6
50.2 51.5
46.9 50.2
47.8 49.9
49.3 49.8
53.1 49.3
49.5 50.1
To determine whether the bags are indeed being underfilled by the machinery, the
manager must conduct a test of mean with a significance level α = 0.05.
In a minimum of 175 words, respond to the following:
 State appropriate null (Ho) and alternative (H1) hypotheses.
 What is the critical value if we work with a significant level α = 0.05?
 What is the decision rule?
 Calculate the test statistic.
 Are the bags indeed being underfilled?

5.  Should machinery be recalibrated?
Due Monday
Reply to at least 2 of your classmates or your faculty member. Be constructive and
professional in your responses.
For More Classes Please Visit
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DAT 565 Wk 5 Discussion - Patterns and Modeling
Post a total of 3 substantive responses over 2 separate days for full participation.
This includes your initial post and 2 replies to other students or your faculty member.
Due Thursday
Respond to the following in a minimum of 175 words:
Models help us describe and summarize relationships between variables. Understanding
how process variables relate to each other helps businesses predict and improve
performance. For example, a marketing manager might be interested in modeling the
relationship between advertisement expenditures and sales revenues.
Consider the dataset belowand respond to the questions that follow:
Advertisement ($'000) Sales ($'000)
1068 4489
1026 5611
767 3290
885 4113
1156 4883
1146 5425
892 4414

6. 938 5506
769 3346
677 3673
1184 6542
1009 5088
 Construct a scatter plot with this data.
 Do you observe a relationship between both variables?
 Use Excel to fit a linear regression line to the data. What is the fitted regression
model? (Hint: You can follow the steps outlined on page 497 of the textbook.)
 What is the slope? What does the slope tell us?Is the slope significant?
 What is the intercept? Is it meaningful?
 What is the value of the regression coefficient,r? What is the value of the
coefficient of determination, r^2? What does r^2 tell us?
 Use the model to predict sales and the business spends $950,000 in
advertisement. Does the model underestimate or overestimates ales?
Due Monday
Reply to at least 2 of your classmates or your faculty member. Be constructive and
professional.
For More Classes Please Visit
http://www.uopstudy.com/
DAT 565 Wk 6 Discussion - Time Series Modeling
Post a total of 3 substantive responses over 2 separate days for full participation.
This includes your initial post and 2 replies to other students or your faculty member.
Due Thursday
Time series are particularly useful to track variables such as revenues, costs, and profits
over time. Time series models help evaluate performance and make predictions. Consider
the following and respond in a minimum of 175 words:

7.  Time series decomposition seeks to separate the time series (Y) into 4
components: trend (T), cycle (C), seasonal (S), and irregular (I). What is the difference
between these components?
 The model can be additive or multiplicative.When we do use an additive model?
When do we use a multiplicative model?
 The following list gives the gross federal debt(in millions of dollars) for the U.S.
every 5 years from 1945 to 2000:
Year Gross Federal Debt ($millions)
1945 260,123
1950 256,853
1955 274,366
1960 290,525
1965 322,318
1970 380,921
1975 541,925
1980 909,050
1985 1,817,521
1990 3,206,564
1995 4,921,005
2000 5,686,338
 Construct a scatter plot with this data. Do you observe a trend? If so, what type of
trend do you observe?
 Use Excel to fit a linear trend and an exponential trend to the data. Display the
models and their respective r^2.
 Interpret both models. Which model seems to be more appropriate? Why?
Due Monday
Reply to at least 2 of your classmates or your faculty member. Be constructive and
professional.