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Discussions 1.Correlation What results in your departments seem to be correlated or related (either causal or not) to other activities? How could you verify this? What are the managerial implications of a correlation between these variables? 2.Regression At times we can generate a regression equation to explain outcomes. For example, an employee's salary can often be explained by their pay grade, appraisal rating, education level, etc. What variables might explain or predict an outcome in your department or life? If you generated a regression equation, how would you interpret it and the residuals from it?
For the following cases, determine whether the sampling is dependent or independent. Explain your conclusion.
How should I compute probability in spss for variable "seizure duration" with unnormal distribution which constitutes numerical data of duration in seconds.
Find the sample proportions and test statistic for equal proportions. Is the decision close? Find the p-value.
Which salesperson should be assigned to each region to minimize total time? Identify the optimal assignments and compute total minimum time.
Describe the types of decisions that do not involve uncertainty and risk and common approaches used for analyzying them.
According to Chebyshev's Theorem, how many students scored between 23 and 95?
Analyze the process of statistical quality control and determine which part of the process would be most difficult and what steps could be taken to mitigate the anticipated difficulty.
Assume that the process is in control and that the population of all jar fills is normally distributed.
What is the probability that a single, randomly selected piece of material will be defective? (Give the answer to two decimal places.)
Construct a 90 percent confidence interval for the proportion of all kernels that would not pop. (b) Check the normality assumption. (c) Try the Very Quick Rule.
Following are speeds of 40 cars clocked by radar on a particular road in a 35-mph zone on a particular afternoon; Make (a) a frequency table, (b) a histogram, and (c) a frequency polygon. Then describe the general shape of the distribution.
At a large university, 500 freshmen take their final exam for their marketing course. Scores are normally distributed with a mean 79 and standard deviation 7.
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