Summary BMAL 590 Quantitative Research Techniques Questions (solved to Pass).

BMAL 590 Quantitative Research Techniques Questions (solved to Pass).You take a random sample of 100 students at your university and find that their average GPA is 3.1. If you use this information to help you estimate the average GPA for all students at your university, then you are doing what branch of statistics? Descriptive statistics Inferential statistics Sample statistics Population statistics -A company has developed a new computer sound card whose average lifetime is unknown. In order to estimate this average, 200 sound cards are randomly selected from a large production line and tested; their average lifetime is found to be 5 years. The 200 sound cards represent a parameter. statistic. sample. population. -A company has developed a new computer sound card whose average lifetime is unknown. In order to estimate this average, 200 sound cards are randomly selected from a large production line and tested; their average lifetime is found to be 5 years. The five years represents a parameter. statistic. sample. population. -A summary measure that is computed from a population is called a sample. statistic. population. parameter. -Which of the following is a measure of the reliability of a statistical inference? A population parameter. A significance level. A descriptive statistic. A sample statistic. -The process of using sample statistics to draw conclusions about population parameters is called finding the significance level. calculating descriptive statistics. doing inferential statistics. calculating the confidence level. -Which of the following represents a population, as opposed to a sample? 1,000 respondents to a magazine survey which has 500,000 subscribers. The first 10 students in your class completing a final exam. Every fifth student to arrive at the book store on your campus. All registered voters in the State of Michigan. -A study in under way to determine the average height of all 32,000 adult pine trees in a certain national forest. The heights of 500 randomly selected adult pine trees are measured and analyzed. The sample in this study is the average height of the 500 randomly selected adult pine trees. the average height of all the adult pine trees in this forest. all adult pine trees in this forest. the 500 adult pine trees selected at random selected at random from this forest. -The significance level of a statistical inference measures the proportion of times a conclusion about a population will be correct in the long run. the proportion of times a conclusion about a population will be wrong in the long run. the proportion of times an estimation procedure will be correct in the long run. the proportion of times an estimation procedure will be wrong in the long run. -The confidence level of a statistical inference measures the proportion of times a conclusion about a population will be correct in the long run. the proportion of times a conclusion about a population will be wrong in the long run. the proportion of times an estimation procedure will be correct in the long run. the proportion of times an estimation procedure will be wrong in the long run. -A marketing research firm selects a random sample of adults and asks them a list of questions regarding their beverage preferences. What type of data collection is involved here? An experiment. A survey. Direct observation. None of these choices -Which of the following statements is true regarding the design of a good survey? The questions should be kept as short as possible. A mixture of dichotomous, multiple-choice, and open-ended questions may be used. Leading questions must be avoided. All of these choices are true. -Which method of data collection is involved when a researcher counts and records the number of students wearing backpacks on campus on a given day? An experiment. A survey. Direct observation. None of these choices. -The difference between a sample mean and the population mean is called nonresponse error. selection bias. sampling error. nonsampling error. -The manager of the customer service division of a major consumer electronics company is interested in determining whether the customers who have purchased a videocassette recorder over the past 12 months are satisfied with their products. If there are four different brands of videocassette recorders made by the company, the best sampling strategy would be to use a simple random sample. stratified random sample. cluster sample. self-selected sample. -When every possible sample with the same number of observations is equally likely to be chosen, the result is called a simple random sample. stratified random sample. cluster sample. biased sample. -Which of the following types of samples is almost always biased? Simple random samples. Stratified random samples. Cluster samples. Self-selected samples. -Which of the following is an example of a nonsampling error? Some incorrect responses are recorded. Responses are not obtained from all members of the sample. Some members of the target population cannot possibly be selected for the sample. All of these choices are true. -Which of the following situations lends itself to cluster samples? When it is difficult to develop a complete list of the population members. When the population members are widely disbursed. When selecting and collecting data from a simple random sample is too costly. All of these choices are true. -Which of the following causes sampling error? Taking a random sample from a population instead of studying the entire population. Making a mistake in the process of collecting the data. Nonresponse bias. All of these choices are true. -Which of the following describes selection bias? A leading question is selected for inclusion in the survey. Some members of the target population are excluded from possible selection for the sample. A person selected for the sample has a biased opinion about the survey. All of these choices are true. -An approach of assigning probabilities which assumes that all outcomes of the experiment are equally likely is referred to as the subjective approach. objective approach. classical approach. relative frequency approach. -The collection of all possible outcomes of an experiment is called a simple event. a sample space. a sample. a population. -If event A and event B cannot occur at the same time, then A and B are said to be mutually exclusive. independent. collectively exhaustive. None of these choices. -Which of the following best describes the concept of marginal probability? It is a measure of the likelihood that a particular event will occur, regardless of whether another event occurs. It is a measure of the likelihood that a particular event will occur, if another event has already occurred. It is a measure of the likelihood of the simultaneous occurrence of two or more events. None of these choices. -The intersection of events A and B is the event that occurs when either A or B occurs but not both. neither A nor B occur. both A and B occur. All of these choices are true. -If the outcome of event A is not affected by event B, then events A and B are said to be mutually exclusive. independent. collectively exhaustive. None of these choices. -Suppose P(A) = 0.35. The probability of the complement of A is 0.35. 0.65. -0.35 None of these choices. -If the events A and B are independent with P(A)=0.30 and P(B)=0.40, then the probability that both events will occur simultaneously is 0 0.12. 0.70. Not enough information to tell. -If A and B are mutually exclusive events with P(A) = 0.30 and P(B)=0.40, then P(A or B) is 0.10. 0.12. 0.70. None of these choices. -Bayes' Law is used to compute prior probabilities. joint probabilities. union probabilities. posterior probabilities. -Initial estimates of the probabilities of events are known as joint probabilities. posterior probabilities. prior probabilities. conditional probabilities. -The standard deviation of the sampling distribution of x̄is also called the central limit theorem. standard error of the sample mean. finite population correction factor. population standard deviation -The Central Limit Theorem states that, if a random sample of size n is drawn from a population, then the sampling distribution of the sample mean is approximately normal if n > 30 . is approximately normal if n < 30 . is approximately normal if the underlying population is normal. None of these choices. -If all possible samples of size n are drawn from a population, the probability distribution of the sample mean x̄ is called the standard error of x̄. the expected value of x̄. the sampling distribution of x̄. he normal distribution. -Sampling distributions describe the distributions of population parameters. sample statistics. both parameters and statistics None of these choices. -Suppose X has a distribution that is not normal. The Central Limit Theorem is important in this case because t says the sampling distribution of x̄is approximately normal for any sample size. it says the sampling distribution of x̄is approximately normal if n is large enough. it says the sampling distribution of x̄is exactly normal, for any sample size. None of these choices. -As a general rule, the normal distribution is used to approximate the sampling distribution of the sample proportion only if the sample size n is greater than 30. the population proportion p is close to 0.50. the underlying population is normal. np and n(1 - p) are both greater than or equal to 5. The standard deviation of p̂ is also called the standard error of the sample proportion. standard deviation of the population. standard deviation of the binomial. None of these choices. -If two populations are normally distributed, the sampling distribution of the difference in the sample means, x̄1 – x̄2 is approximately normal for any sample sizes. approximately normal if both sample sizes are large. exactly normal for any sample sizes. exactly normal only if both sample sizes are large. -If two random samples of sizes n1 and n2 are selected independently from two populations with means μ1 and μ2, then the mean of x̄1 - x̄2 equals μ1 + μ 2 μ1 - μ 2 μ1 / μ 2 μ1 μ2 -If two random samples of sizes n1 and n2 are selected independently from two non-normally distributed populations, then the sampling distribution of the sample mean difference, x̄1 - x̄2 is always non-normal. is always normal. is approximately normal only if n1 and n2 are both larger than or equal to 30. is approximately normal regardless of n1 and n2. -The standard deviation of x̄1 - x̄2 is also called the standard error of the difference between two sample means. standard deviation of the difference between the population means. normal approximation to the difference of two binomial random variables. None of these choices. -The hypothesis of most interest to the researcher is the alternative hypothesis. the null hypothesis. both hypotheses are of equal interest. Neither hypothesis is of interest. - Type I error occurs when we reject a false null hypothesis. reject a true null hypothesis. don't reject a false null hypothesis. don't reject a true null hypothesis. -A Type II error is defined as rejecting a true null hypothesis. rejecting a false null hypothesis. not rejecting a true null hypothesis. not rejecting a false null hypothesis. -Which of the following probabilities is equal to the significance level α? Probability of making a Type I error. Probability of making a Type II error. Probability of rejecting H0 when you are supposed to. Probability of not rejecting H0 when you shouldn't. -If we reject the null hypothesis, we conclude that there is enough statistical evidence to infer that the alternative hypothesis is true. here is not enough statistical evidence to infer that the alternative hypothesis is true. there is enough statistical evidence to infer that the null hypothesis is true. there is not enough statistical evidence to infer that the null hypothesis is true.