Exam 11: Population Estimates and Hypothesis Testing

If you were investigating the average number of golf balls purchased by golfers in a month, your sample statistic would be a mean.

The proper command sequence in XL Data Analyst to generate a confidence interval for a percentage is:

Statisticians make estimates of population parameters that may be either:

The most commonly used level of confidence in marketing research is the 95% level, corresponding to 1.96 standard errors.

Roman letters, such as s, p, and x, are typically used to represent:

Which of the following is NOT used to test hypotheses?

The standard error of the average is determined by dividing the standard deviation from the same sample that yielded the average by the square root of the sample size.

Values computed with sample data are referred to as:

When following the five (5) steps to calculate the confidence interval estimate of a population percentage, the only thing that differs between the 95% confidence interval computations and the 99% confidence interval computations is the z value.

If we are testing a hypothesis that a sample mean does not differ from a hypothesized value at the 95 percent level of confidence, and we arrive at a z value of 1.99, we would fail to support the hypothesis.

Sample information is invariably more accurate than a hypothesis.

The standard error of the average is _________ with more variability and _________ with large samples.

Daniel Jean-Baptiste is the brand manager for Healthy-Pick Cookies, Inc. Daniel had been through the new product development process and has developed a new cookie that has very good taste and texture, yet has no calories, fat, sodium, or cholesterol. Concept tests on the product have been excellent and now Daniel is ready to test market the new cookie and has selected Vancouver, British Columbia, as his first test city. But before he starts the test market, Daniel wants to conduct a research project that will help him forecast sales, so that he can better prepare production to supply the test market. The project leads to a probability sample in which household members are randomly called and are given a thorough description of the new cookie, including the price and choices of flavours. The key question respondents are asked is how likely it is that they will actually buy the new cookie, and this is measured on a 7-point intensity continuum scale ranging from 1 being "Very Unlikely" to 7 being "Very Likely". Respondents were also asked how many boxes of cookies they would expect to buy in a month. At the end of the study, the researchers tell Daniel that 8 percent of the households contacted stated that they were "Very Likely" to buy the new cookie. In order to get an estimate of the sales potential in the test market Daniel could:

The z value associated with a 95 percent confidence interval is either a + 1.96.

Two types of statistical inference are parameter estimates and hypothesis tests.

A toy store owner hypothesizes, at the 95 percent level of confidence, that parents spend less than $100 on toys per visit to her store. A sample is taken and the hypothesis test shows a z value of -1.65. This means the sample:

With a larger sample size, the range used to estimate the true population value is also larger.

The crux of hypothesis testing is the:

The critical z value for a directional hypothesis test is adjusted downward to 1.46 from 1.96 for the 95% confidence level.

There are five steps involved in computing confidence intervals for a mean or a percentage. One of those steps is to determine the sample finding.