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They believe that people with higher incomes would be more likely both to be interested in a video about potential honeymoon destinations, and to be willing to pay more for such videos. They want you to determine what the data indicate about this. In this problem I am having an issue trying to determine what equation to use to solve. Is this a one or two way ANOVA or should I just use a z-test to solve?
You're asked to determine whether the workers live in the community. Your personnel department provides the following table:
Find the sample size for the 95% confidence interval used to estimate the population proportion.
Which test do we use to see if the difference in our sample is statistically significant? Why? Should it be one or two-tailed?
Recognize and explain potential threats (up to 3) to external validity.
Make a histogram for the r probability distribution.
According to a report by Scarborough Research, the average monthly household cellular phone bill is $73. Suppose local monthly household cell phone bills are normally distributed with a standard deviation of $11.35.
Here is a two-way table showing enrollment data for full-time undergraduate students in U.S. colleges and universities. The entries are thousands of students:
Costs of Televisions Listed below are prices (in dollars) and quality rating scores of rare-projection televisions (based on data from Consumer Reports). All of the televisions have screen sizes of 55 in or 56 in.
Following data represent concentration of dissolved organic carbon (mg/L) collected from 20 samples of organic soil. Sample standard deviation is?
Give a possible description why serum cholesterol values for older males are lower than for younger males and reverse is true for females.
Now we are going to talk about continuous probability distributions. In a continuous probability distribution, the variable can have a value within a range.
The quality control department of Widgets Manufacturing needs your help. They can't decide which significance level is appropriate for testing the claim that fewer than 50% of widgets from a production run are defective.
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