- 1. Any systematic failure of a sampling method to represent its population
A) unbias
B) bias
C) distribution
D) failure
- 2. A sample that consists of the entire population
A) sample
B) statistic
C) census
D) parameter
- 3. Study in which subjects are randomly assigned to treatments
A) survey
B) frequency
C) experiment
D) sample
- 4. Variable whose levels are controlled by the experimenter
A) factor
B) level
C) subject
D) variable
- 5. Type of study in which subjects who are similar in ways not under study may be grouped together and then compared with each other on the variables of interest
A) matched pair
B) stratified
C) cluster
D) random
- 6. Sampling design in which the population is divided into several groups by a characteristic, and random samples are then drawn from each stratum
A) random
B) matched pair
C) stratified
D) cluster
- 7. Sampling design in which entire group is split into split into similar parts and then a few of them are chosen at random where every member is sampled
A) stratified
B) random
C) matched pair
D) cluster
- 8. Sampling schemes that combine several sampling methods
A) multistage
B) stratified
C) cluster
D) matched pair
- 9. Type of bias that is problematic because the intended sample is incomplete
A) voluntary response
B) undercoverage
C) confounding
D) nonresponse
- 10. Sample drawn by select an individual from a list and then each of the next N individuals from the sampling frame
A) multistage
B) systematic
C) cluster
D) matched pair
- 11. Type of bias that is problematic because some groups are not represented in the sample
A) undercoverage
B) confounding
C) nonresponse
D) voluntary response
- 12. Type of bias that is problematic because those who volunteer tend to have strong negative opinions
A) undercoverage
B) convenience
C) voluntary response
D) confounding
- 13. A type of response bias where the question is posed to achieve a desired result
A) voluntary response
B) bad question
C) wording bias
D) nonresponse
- 14. Sampling design where individuals are chosen based on who is easily available
A) convenience
B) nonresponse
C) census
D) voluntary response
- 15. When the levels of one factor are associated with the levels of another factor so their effects cannot be separated
A) level
B) wording bias
C) confounding
D) lurking variable
- 16. Neither the subjects nor the people who have contact with them know which treatment a subject has received
A) block design
B) double blind
C) confounding
D) matched pair
- 17. Study based on data in which no treatments have been assigned to subjects
A) survey
B) observational study
C) experiment
D) block
- 18. The tendency of many human subjects to show a response even when administered a fake treatment
A) placebo effect
B) lurking variable
C) confounding
D) random
- 19. Sampling design in which each set of n elements in the population has an equal chance of selection
A) block
B) voluntary
C) random
D) cluster
- 20. When an observed difference is too large to believe that it is likely to have occurred naturally
A) outlier
B) statistically significance
C) great result
D) force of nature
- 21. A variable other than x and y that simultaneously affects both variables, accounting for the correlation between the two
A) lurking variable
B) nonresponse
C) placebo
D) confounding
- 22. The probability of getting a result at least as extreme as the result given from the test. The lower the value the stronger the evidence.
A) p-value
B) z-score
C) distribution
D) frequency
- 23. States that, in a normal distribution, about 68% of the terms are within one standard deviation of the mean, about 95% are within two standard deviations, and about 99.7% are within three standard deviations (normal curve).
A) empirical rule
B) statistically significance
C) central limit theorem
D) distribution
- 24. The hypothesis that states there is no difference between two or more sets of data in a significance test.
A) null hypothesis
B) alternative hypothesis
- 25. The likelihood that a particular event will occur
A) distribution
B) probability
C) frequency
- 26. Statistical procedures used to describe characteristics and responses of groups of subjects
A) simple random sample
B) descriptive statistics
C) central measures of tendancey
D) variable
- 27. The middle score in a distribution; half the scores are above it and half are below it
A) mode
B) median
C) mean
D) center
- 28. A graphical representation of a quantitative data set. Leading values of each data point are presented as stems and second digits are given as leaves
A) boxplot
B) normal distribution
C) scatterplot
D) stemplot
- 29. The range of percentage points in which the sample accurately reflects the population, the range surrounding a sample's response within which researchers are confident the larger population's true response would fall
A) margin of error
B) confidence level
C) range
D) confidence interval
- 30. The distribution of values taken by the statistic in all possible samples of the same size from the same population
A) frequency distribution
B) simple random sample
C) sampling distribution
D) conditional probability
- 31. Data identified by something other than numbers
A) qualitative
B) quantitative
- 32. Data identified by a numerical value
A) quantitative
B) qualitative
- 33. An error that occurs when a researcher concludes that the independent variable had no effect on the dependent variable, when in truth it did; a false negative
A) type II
B) type I
- 34. The probability that a particular event will occur, given that another event has already occurred
A) placebo effect
B) conditional probability
C) life
D) frequency
- 35. The datum which occurs the most in a set of data
A) mode
B) center
C) mean
D) median
- 36. The arithmetic average of a distribution, obtained by adding the scores and then dividing by the number of scores
A) median
B) mean
C) mode
D) center
- 37. A measure of variability that describes an average distance of every score from the mean (r
A) margin of error
B) spread
C) standard deviation
D) variation
- 38. The hypothesis which states the Null Hypothesis is incorrect in a significance test
A) null hypothesis
B) alternative hypothesis
- 39. Law stating that a large number of items taken at random from a population will (on the average) have the population statistics
A) law of large numbers
B) central limit theorem
C) law of statistics
D) law of many data points
- 40. The measure of a relationship between two variables or sets of data
A) range
B) z-score
C) correlation
D) coefficient of determination
- 41. Measures the percentage of variation in a dependent variable explained by one or more independent variables (r2)
A) correlation coefficient
B) range
C) coefficient of determination
- 42. An experiment in which a set number of trials is used
A) binomial experiment
B) geometric experiment
C) normal experiment
- 43. An extreme deviation from the mean
A) variation
B) standard deviation
C) outlier
D) data point
- 44. Estimating a value outside the range of measured data
A) empirical rule
B) prediction
C) confidence interval
D) extrapolation
- 45. A relationship between two sets of data or two datum which states the outcome of one has no effect on the outcome of the other.
A) control
B) independent
C) dependent
D) placebo
- 46. Range of the middle 50% of the values; Q3-Q1 = 75th percentile - 25th percentile
A) interquartile range
B) standard deviation
C) range
D) variation
- 47. The range of values within which a population parameter is estimated to lie
A) range
B) interquartile range
C) critical level
D) confidence interval
- 48. The standard deviation of a sampling distribution
A) standard error
B) standard deviation of a sample
C) variation
- 49. The difference between an observed value of the response variable and the value predicted by the regression line
A) residual
B) prediction
C) line of best fit
- 50. A parameter of the t distribution. When the t distribution is used in the computation of an interval estimate of a population mean, the appropriate t distribution has n-1 degrees of freedom, where n is the size of the simple random sample
A) degree of freedom
B) sample data
C) sample size
D) central limit theorem
- 51. An experiment in which there is no set number of trials but is ended by achieving an outcome
A) normal experiment
B) geometric experiment
C) binomial experiment
- 52. A descriptive feature in which describes the range of the data graphically
A) mode
B) median
C) mean
D) spread
- 53. Variable where the number of outcomes can be counted and each outcome has a measurable and positive probability
A) discrete random variable
B) control variable
C) continuous variable
- 54. The sampling distribution of the mean will approach the normal distribution as n increases (n>30)
A) law of large numbers
B) central limit theorem
C) placebo effect
D) rule of thumb number 1
- 55. An error that occurs when a researcher concludes that the independent variable had an effect on the dependent variable, when no such relation exists; a false positive
A) type II
B) type I
- 56. Displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values
A) scatterplot
B) stemplot
C) distribution
D) boxplot
- 57. Each event or variable is independent from one another. No event or variable will have an effect on the probability of outcome for any other event or variable
A) independent
B) mutually exclusive
- 58. A cause and effect relationship in which one variable controls the changes in another variable
A) causation
B) placebo
C) lurking variable
D) experiment
- 59. A parametric inferential statistical test of the null hypothesis for a single sample where the population standard deviation is known
A) z-test
B) t-test
- 60. A parametric inferential statistical test of the null hypothesis for a single sample where the population standard deviation is unknown
A) z-test
B) t-test
- 61. Uses sample data to test hypotheses about the shape or proportions of a population distribution. The test determines how well the obtained sample proportions fit the population proportions specified by the null hypothesis
A) hi-Squared Homogenity
B) Chi-Squared Goodness of Fit
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