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A hypothesis states a difference exists between two populations. Sometimes this is an obvious conclusion because the means will be very different. For example, if I gave a math tests to boys and girls and the boys on average scored 20 points better than the girls, I know that is enough of a difference to conclude with accuracy that boys are in fact better in math than girls. And I know that a mere 1 or 2 point difference is not enough of a difference to conclude that boys or girls are better. But what if the difference is 5 or 10 points - is that enough of a difference? Now it is not so obvious = and that's why we need to do the t-test.
Can someone give me an example of when you thought something mattered - that it made a difference, but later you were surprised to learn that what you thought mattered, did not. Or an example of time when something did not matter, when in fact, all along it did. Thanks for sharing.
Construct a 95% confidence interval for the proportion of votes that Jefferson will receive, and make a conclusion about Jefferson winning election.
From past experience, an automobile insurance company knows that a given automobile will suffer a total loss with probability .02, a 50% loss with probability .08, or a 25% loss with probability .15 during a year.
Intersection of two mutually exclusive events: can be any value between 0 to 1, must always be equal to 1.
How many participants need to be enrolled in each group to have 90% chance of detecting a significant difference using a two-sided test with a a= .05 if compliance is perfect?
Compute the 95% confidence interval around the mean of each of the three groups and plot the confidence interval in the space provided above.
A pair of dice is rolled. What is the probability of each of the following? (Round your answers to three decimal places.)
What level of confidence is associated with an interval of .400513 to .515487 for the long run proportion of new product placements?
Todd is less interested in testing a hypothesis than he is in developing an estimate for what people would be willing to pay. He would like 95% confidence intervals for the average price people would be willing to pay
A chance sample of 50 families revealed an average or median of $112,000 and a standard deviation of $40,000. What is the standard error of the average or median?
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.
The population mean of a company's racing bicycles is 9.07 kg (20.0 lb) with a population standard deviation of 0.40 kg. If the distribution is approximately normal
Suppose that 20 minutes are selected independently and weighted. Let Y equal the number of these mints that weigh less than 30 grams.
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