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1. What characterizes a regular definition (dictionary) and an operational definition?
2. What is the purpose of sampling?
3. In distributions of populations, please consider Chebyshev's rule and the Empirical Rule. This takes some thinking.
a) When (what kind of a situation) would you use each in business? Why are they important? How are they calculated?
4. However we need to look closer at "causal research". Now concerning causal research let us look deeper: What must we actually show (necessary and sufficient conditions) if we are to prove cause and effect?
5. An important practical consideration when sampling is the sample size. So, what determines sample size? What influences our decisions?
Critically illustrate out the range? What is the arithmetic mean income? What is the population variance?
Describe a business situation that you have had or might face that will benefit from the use of confidence intervals?
We can compare two sample means to determine if the samples were obtained from normal populations with the same mean using the "t" distribution.
A sample of twenty automobiles was taken, and the miles per gallon (MPG), horsepower, and total weight were recorded. Develop a linear regression model to predict MPG using horsepower as the only independent variable. Develop another model with weig..
The moment generating function of normal distributed random variable ,Y, with mean and variance .derive the moment generating function of X=-3Y+4.what is the distribution of X? why?
If the sum of the squared deviations about the regression line is SSE = 40.0, what is the coefficient of determination?
If alpha level is changed from a = 0.05 to a = 0.01. What occurs to boundaries for critical region?
Kay Manning is a sales manager with two salespeople working for her. The ability of each salesperson to secure new accounts has historically been: Jesse Burkett can generate 4 new accounts per 10 visits to prospects
Create Frequency Distribution of Sample Mean. Compute and Identifies Sampling Distribution of Sample Mean.
Stock A has an expected return of 12% and a standard deviation of 40%. Stock B has an expected return of 18% and a standard deviation of 60%. The correlation coefficient between Stocks A and B is 0.2.
Illustrate the maximum number of reservations that it could accept for a flight with a capacity of 160, if it needs the probability of accommodating all reservation holders to be at least 95%.
Regression model results can be erroneous if multicollinearity is an issue. What causes multicollinearity? If the intercept is statistically significant, what does this tell you?
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