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Bus Stats Vocab
Vocab words for business statistics class
| Question | Answer |
|---|---|
| The science of collecting, organizing, presenting, analyzing, and interpreting data to assist in making more effective decisions. | Statistics |
| The entire set of individuals or objects of interest or the measurements obtained from all individuals or objects of interest. | Population |
| A portion, or part, of the population of interest. | Sample |
| Methods of organizing, summarizing, and presenting data in an informative way. | Descriptive Statistics |
| The methods used to estimate a property of a population on the basis of a sample. | Inferential Statistics |
| A chart that shows the proportion or percent that each class represents of the total number of frequencies. | Pie Chart |
| A grouping of QUALITATIVE data into mutually exclusive classes showing the number of observations in each class. | Frequency Table |
| A grouping of data into mutually exclusive classes showing the number of observations in each class. | Frequency Distrobution |
| A graph is which the classes are marked on the horizontal axis and the class frequencies on the vertical axis. The class frequencies are represented by the heights of the bars and the bars are drawn adjacent to each other. | Histogram |
| A graph in which the classes are reported on the horizontal axis and the class frequencies on the vertical axis. | Bar Chart |
| A characteristic of a population. | Parameter |
| A characteristic of a sample. | Statistic |
| The midpoint of the values after they have been ordered from the smallest to the largest, or the largest to the smallest. | Median |
| The value of the observation that appears most frequently. | Mode |
| The difference between the largest and smallest values in a data set. | Range (Range = Largest value – Smallest value) |
| The arithmetic mean of the absolute values of the deviations from the arithmetic mean. | Mean Deviation |
| The arithmetic mean of the squared deviations from the mean. | Variance |
| The square root of the variance. | Standard Deviation |
| For any set of observations (sample or population), the proportion of the values that lie within k standard deviations of the mean is at least 1-1/k^2 where K is any constant greater than 1. | Chebyshev's Theorem |
| ... approximately 68 percent of the observations will lie within plus and minus one standard deviation of the mean; about 95 percent of the observations will lie within... (99.7%) will lie within plus and minus three standard deviations of the mean. | Empirical Rule |
| A value between zero and one, inclusive, describing the relative possibility (chance or likelihood) an event will occur. | Probability |
| A process that leads to the occurrence of one and only one of several possible observations. | Experiment |
| A particular result of an experiment. | Outcome |
| A collection of one or more outcomes of an experiment. | Event |
| The occurrence of one event means that none of the other events can occur at the same time. | Mutually Exclusive |
| At least one of the events must occur when an experiment is conducted. | Collectively Exhaustive |
| The probability of an event happening is the fraction of the time similar events happened in the past. | Empirical Probability |
| Over a large number of trials the empirical probability of an event will approach its true probability. | Law of Large Numbers |
| A probability that measures the likelihood two or more events will happen concurrently. | Joint Probability |
| The occurrence of one event has no effect on the probability of the occurrence of another event. | Independence |
| The probability of a particular event occurring, given another event has occurred. | Conditional Probability |
| A table used to classify sample observations according to two or more identifiable characteristics. | Contingency Table |
| If there are M ways of doing one thing and N ways of doing another thing, there and M x N ways of doing both. | Multiplication Formula |
| The likelihood (probability) of a particular event happening that is assigned by an individual based on whatever information is available. | Subjective Concept of Probability |
| Any arrangement of r objects selected from a single group of n possible objects. | Permutation |
| A listing of all the outcomes of an experiment and the probability associated with each outcome. | Probability Distribution |
| A quantity resulting from an experiment that, by chance, can assume different values. | Random Variable |
| A random variable that can assume only certain clearly separated values. | Discrete Random Variable |
| The signed distance between a selected value, designated X, and the mean, μ, divided by the standard deviation, σ. | z Value |
| A random starting point is selected, and then every kth member of the population is selected. | Systematic Random Sample |
| A population is divided into subgroups, and a sample is randomly selected from each group. | Stratified Random Sample |
| A population is divided into groups using naturally occurring geographic or other boundaries. Then, groups are randomly selected and a sample is collected by randomly selecting from each group. | Cluster Sample |
| A sample selected so that each item or person in the population has the same chance of being included. | Simple Random Sample |
| The difference between a sample statistic and its corresponding population parameter. | Sampling Error |
| A probability distribution of all possible sample means of a given sample size. | Sampling Distribution of the Sample Mean |
| A probability distribution of all possible sample means of a given sample size. | Sampling Distribution of the Sample Mean |
| If all samples of a particular size are selected from any population, the sampling distribution of the sample mean is approximately a normal distribution. This approximation improves with larger samples. | Central Limit Theorem |
| The statistic, computed from sample information, which is used to estimate the population parameter. | Point Estimate |
| A range of values constructed from sample data so that the population parameter is likely to occur within that range at a specified probability. | Confidence Interval |
| The fraction, ratio, or percent indicating the part of the sample or the population having a particular trait of interest. | Proportion |
| A statement about a population parameter subject to verification. | Hypothesis |
| A procedure based on sample evidence and probability theory to determine whether the hypothesis is a reasonable statement. | Hypothesis Testing |
| A statement about the value of a population parameter developed for the purpose of testing numerical evidence. | Null Hypothesis |
| A statement that is accepted if the sample data provide sufficient evidence that the null hypothesis is false. | Alternative Hypothesis |
| The probability of rejecting the null hypothesis when it is true. | Level of Significance |
| Rejecting the null hypothesis when it is true. | Type I Error |
| Accepting the null hypothesis when it is false. | Type II Error |
| A value, determined from sample information, used to determine whether to reject the null hypothesis. | Test Statistic |
| The probability of making a Type I error. | Alpha |
| The probability of making a Type II error. | Beta |
| The dividing point between the region where the null hypothesis is rejected and the region where it is not rejected. | Critical Value |
| The probability of observing a sample value as extreme as, or more extreme than, the value observed, given that the null hypothesis is true. | p-Value |
| The sum of the squared differences between each observation and the overall mean. | Total Variation |
| The sum of the squared differences between each treatment mean and the grand or overall mean. | Treatment Variation |
| The sum of the squared differences between each observation and its treatment mean. | Random Variation |
| A group of techniques to measure the association between two variables. | Correlation Analysis |
| The variable that is being predicted or estimated. It is scaled on the Y-axis. | Dependent Variable |
| The variable that provides the basis for estimation. It is the predictor variable. It is scaled on the X-axis. | Independent Variable |
| A measure of the strength of the linear relationship between two variables. | Coefficient of Correlation |
| The proportion of the total variation in the dependent variable Y that is explained, or accounted for, by the variation in the independent variable X. | Coefficient of Determination |
| An equation that expresses the linear relationship between two variables. | Regression Equation |
| Determining a regression equation by minimizing the sum of the squares of the vertical distances between the actual Y values and the predicted values of Y. | Least Squares Principle |
| A measure of the dispersion, or scatter, of the observed values around the line of regression. | Standard Error of Estimate |
Created by:
joshpmccarthy
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