Business Statistics Glossary for Job Interview
Analysis of variance (ANOVA): A procedure for determining how much of the total variability among scores to attribute to a range of sources of variation and for testing hypotheses concerning some of the sources
Completely randomized design (CRD): A study in which the assignment of participants to treatment levels is completely random; each participant is in only one treatment condition
Confidence interval: A range of values computed from data so that a specified percentage (often 95%) of all possible random samples from the same population will give intervals that contain the true population value
Correlation coefficient: A number that represents the degree of association or strength of the relationship between two variables
Critical region: The region for rejecting the null hypothesis; determined by H A and α
Cumulative frequency distribution: A distribution that shows the number, proportion, or percentage of scores that occur below the real upper limit of each interval (including all intervals below)
Dependent samples: The selection of participants in one sample is affected by the selection of participants in the other sample; keywords “matched” or “repeated”
Matched sample: matching each participant in the experimental condition with a participant in the control condition on some variable that is correlated with the dependent variable
Repeated measures: observing the same participants under both the experimental and control conditions
Histogram: Similar to a bar graph, but used for quantitative variables; constructed by placing vertical bars over the real limits of each interval, with the height of each bar corresponding to the frequency of the interval
Independent samples: The selection of participants in one sample is not affected by the selection of participants in the other sample; keyword “random”
Level of significance: The probability that is the largest risk a researcher is willing to take of rejecting a true null hypothesis
Mean: Average; sum of the scores divided by the number of scores
Median: The middle value that divides the data into two equal groups
Mode: The score or qualitative category that occurs with the greatest frequency
Normal distribution: A probability distribution that is unimodal and symmetrical; the mean, median, and mode are all the same value (the highest point on the curve)
Outliers: Scores that differ so markedly from the main body of data that their accuracy is questioned
p-value: The probability of obtaining a value of the test statistic is equal to or more extreme than that observed, given that the null hypothesis is true
Parameter: Descriptive measure for a population; usually represented by Greek letters
Percentile (point): A point on the measurement scale below which a specified percentage of scores falls
Percentile rank: The percentage of the scores of the distribution that fall below that score
Population: The collection of all people, objects, or events having one or more specified characteristics
Power: The probability of correctly rejecting the null hypothesis; 1 – β
Random assignment: The method of placing participants into the treatment groups in which each participant has an equal chance of being placed in any of the groups
Random sampling: The method of drawing samples from a population such that every possible sample of a particular size has an equal chance of being selected
Relative frequency distribution: A distribution that shows the proportion or percent frequency for each interval
Residual (prediction error): The difference between a person’s actual score and predicted score
Sample: A subset of a population
Sampling distribution: A probability distribution in which the random variable is a statistic based on the results of more than one trial
Semi-interquartile range: Half the distance between the first quartile point and the third quartile point
Standard deviation: Measure of the spread of data that is based on every score in a distribution
Standard score: A number that expresses the value of a score relative to the mean and standard deviation of its distribution
Skewed distributions: Distributions that are asymmetrical; there are two types
- Negatively skewed: longer tail extends to the left
- Positively skewed: longer tail extends to the right
Statistic: Descriptive measure for a sample; usually represented by English letters
Type I error: Rejecting a true null hypothesis
Type II error: Retaining a false null hypothesis
