BAD 2323 – Business Statistics Final Exam Study Guide • Margin of error – The value added to and subtracted from a point estimate in order to develop

BAD 2323 – Business Statistics
Final Exam Study Guide
• Margin of error – The value added to and subtracted from a point estimate in order to
develop an interval estimate of the population parameter (Chapter 8)
• To compute an interval estimate for the difference between the means of two
populations, the t distribution is not restricted to small sample situations. (Chapter 10)
• Standard normal distribution the mean is 0 and the standard deviation is 1. (Chapter 6)
• Parameters are numerical characteristics of a population. (Chapter 7)
• A hypothesis is an assumption made about the value of a population parameter.
(Chapter 9)
• The ANOVA procedure is a statistical approach for determining whether or not the
means of three or more populations. (Chapter 13)
• A factor is the independent variable of interest in an ANOVA procedure. (Chapter 13)
• In the ANOVA, treatments refer to different levels of a factor. (Chapter 13)
• If there are three or more populations, then it is possible to test for equality of three or
more population proportions. (Chapter 12)
• A chi-square distribution is the sampling distribution used when making inferences
about a single population’s variance. (Chapter 11)
• A multinomial population is a population where each of its elements is assigned to one
and only one of several classes or categories. (Chapter 12)
• The sample distribution for a goodness of fit test is the chi-square distribution. (Chapter
12)
• In Chapter 6, study the characteristics of the standard normal probability distribution
(e.g., the mean, median, and the mode are not equal)
• Normal probability distribution can have the mean of any numerical value (Chapter 6)
• In developing an interval estimate, if the population standard deviation is unknown, the
sample standard deviation must be used (Chapter 8).

BAD 2323 Business Statistic Online Final Exam Study Guide 2
• The ability of an interval estimate to contain the value of the population parameter is
described by the confidence level. (Chapter 8)
• In general, higher confidence levels provide wider confidence intervals. (Chapter 8)
• The center of a normal curve is the mean of the distribution. (Chapter 6)
• The probability that a continuous random variable takes any specific value is equal to
zero. (Chapter 6)
• A negative value of z indicates that the number of standard deviations of an observation
is to the left of the mean. (Chapter 6)
• The uniform, normal, and exponential distributions are all continuous probability
distributions. (Chapter 6)
• Convenience sampling is an example of nonprobabilistic sampling. (Chapter 7)
• The closer the sample mean is to the population mean, the smaller the sampling error.
(Chapter 7)
• As the sample size increases, the standard error of the mean decreases. (Chapter 7)
• Convenience sampling does not lead to probability samples (Chapter 7) know what leads
to probability samples (e.g., cluster sampling, systematic sampling).
• A probability distribution of all possible values of a sample statistic is known as a
sampling distribution. (Chapter 7)
• In hypothesis testing, the tentative assumption about the population parameter is the
null hypothesis (Chapter 9).
• The power curve provides the probability of correctly rejecting the null hypothesis.
(Chapter 9)
• As the test statistic becomes larger, the p-value gets smaller. (Chapter 9)
• An important application of the chi-square distribution is making inferences about a
single population variance, testing for goodness of fit, and testing for the independence
of two categorical variables (Chapter 12).

BAD 2323 Business Statistic Online Final Exam Study Guide 3
• A statistical test conducted to determine whether to reject or not reject a hypothesized
probability distribution for a population is known as a goodness of fit test. (Chapter 12)
• Marascuilo procedure is used to test for a significant difference between pairs of
population is proportions. (Chapter 12)
• In factorial designs, the response produced when the treatments of one factor interact
with the treatments of another in influencing the response variable is known as
interactions. (Chapter 13)
• The number of times each experimental condition is observed in a factorial design is
known as replication (Chapter 13)
• The mean square is the sum of squares divided by its corresponding degrees of
freedom. (Chapter 13)
• The required condition for using an ANOVA procedure on data from several populations
is that the sampled populations have equal variances. (Chapter 13)