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1. What is meant by time-series data? Give an example.
2. Explain the difference between time-series data and cross-sectional data. Are these two types of data sets mutually exclusive? What do they have in common? How do they differ?
3. What are the differences between quantitative and qualitative forecasting techniques? Under what conditions is it appropriate to use a quantitative technique?
4. Provide an example of a business decision that requires (1) a short-term forecast, (2) a medium-term forecast, and (3) a long-term forecast.
the centers for disease control and prevention reported a survey of randomly selected americans age 65 and older which
Utilize statistical software to conduct data analysis
In our discussions of basic probability theory the concepts of mutually exclusive events and independent events share prominent roles.
the manager of a paint supply store wants to determine whether the mean amount of paint contained in 1-gallon cans
Determine the values of the slack and surplus variables and interpret them. Which constraints are binding constraints? Describe.
Consider babies born in the "normal" range of 37 - 43 weeks gestational age. Extensive data supports the assumption that for such babies born in the United States, birth weight is normally distributed with mean = 3432 grams and standard deviati..
a marketing research firm was hired to estimate the mean prime-lending rate for banks located in the western region of
a two-sample t test is performed with hau1gtu2 and a test statistic of t-1.24 is observed. draw a sketch of the area
A multiple choice test consists of 25 questions with possible answers of a, b, c, d, and e. Estimate the probability that with random guessing, the number of correct answers is between 3 and 10 inclusive.
The following data give birth rates (per 1000 population) for 20 selected states in 1998 (source: The World Almanac and Book of Facts 2000).
Calculate the mean attitude score toward the Springdale Mall shopping area and compute the sample standard deviation. Does this area seem to be well regarded by the respondents?
Suppose the probability of a bank making a mistake in processing a deposit is .0003. If 10,000 deposits (n) are audited, what is the probability that more than 6 mistakes were made in processing deposits?
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