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Business Statistics2
Final Test
| Question | Answer |
|---|---|
| a statistic used to test a hypothesis. | Test Statistic |
| if A and B are two events in a sample space, the union of A and B is the event containing all simple events in A or B or both | Union |
| the variance of a set of n measurements is the average of the squares of the deviations of the measurements about their mean. | Variance |
| Rejecting the null hypothesis when the null hypothesis is true. | Type 1 Error |
| accepting the null hypothesis when the null hypothesis is false and some alternative to the null hypothesis is true | Type 2 Error |
| the standard deviation of a set of n measurements is equal to the positive square root of the variance of the measurements. | Standard Deviation |
| is a discipline that allows researchers to evaluate conclusions derived from sample data. They do it in the form of collecting data, interpreting and analyzing data, and access the reliability of conclusions based on sample data. | Statistics |
| a plot of the pairs of values (x,y) on a rectangular coordinate system, used to assess the relationship between x and y. | Scatter Diagram |
| is a measure of the "steepness" of the line, in the following format y = a + bx | Slope |
| the range of a set of n measurements is the difference between the largest and smallest measurements | Range |
| a procedure for sampling from a population in which (a) the selection of a sample unit is based on chance and (b) every element of the population has a known, nonzero probability of being selected. | Random Sampling |
| a measure of the likelihood that the event will occur. Must have the following, range from 0 to 1 and sum of the probabilities is equal to 1 | Probability |
| the smallest value of alpha for which test results become statistically significant. | P-Value |
| Assume that the elements in a data set are rank ordered from the smallest to the largest. The values that divide a rank-ordered set of elements into 100 equal parts are called percentiles | Percentile |
| A descriptive technique used to exhibit the way in which a single totally quantity is apportioned to a group of categories. Each category is assigned a sector of the circle according to the percentage of the total it represents. | Pie Chart |
| a set of elements that represents all possible outcomes of a statistical experiment. | Sample Space |
| the distribution curve of a frequency distribution. | Ojive |
| one or more observations in a data set that are far in value from the body of the set. Outliers may come from a separate population or may result from sampling or recording errors. | Outlier |
| the chances or likelihood of something happening or being the case | Odds |
| values arranged in ascending order of magnitude | Order Statistic |
| The mode of a set of n measurements is the value of x that occurs with the greatest frequency. The mode is not necessarily unique | Mode |
| a set of n measurements is the value of x that falls in the middle when the measurements are arranged in order of magnitude | Median |
| an average score, often denoted by X-bar. It is the sum of individual scores divided by the number of individuals | Mean |
| In a statistical test of an hypothesis the statement of the hypothesis to be tested | Null Hypothesis |
| If random samples of n observations are drawn from a population with finite mean and standard deviation, then when n is large, the sample mean will be approximately normally distributed with mean and standard deviation. | Central Limit Theorem |
| A given B refers to the probability of occurrence of an event A given that another event B has occurred | Conditional Probability |
| An interval computed from sample values | Confidence Interval |
| A probability associated with a confidence interval that expresses the probability that the interval will include the parameter value under study | Confidence Coefficient - |
| In a statistical test of an hypothesis the value of the test statistic that separates the rejection and acceptance regions | Critical Value |
| The number of linearly independent observations in a set of n observations. The degrees of freedom are equal to n minus the number of restrictions placed on the entire data set | Degrees of Freedom |
| The outcome of an experiment | Event |
| In the theory of testing hypothesis the hypothesis that will be accepted as true if the null hypothesis, Ho, is proved false | Alternative Hypothesis |
| the y intercept is the value of y when x equals zero, denoted as y = a + bx | Y-Intercept |
| Any one of the numbers or values in a series dividing the distribution of the individuals in the series into ten groups of equal frequency | Decile |
| A set of data is said to be discrete if the values / observations belonging to it are distinct and separate | Discrete |
| in a multivariate distribution the probability of one variable taking a specific value irrespective of the values of the others | Marginal Probability |
| The probability that two or more specific outcomes will occur in an event | Joint Probability |
| A measure of the interdependence of two random variables that ranges in value from -1 to +1, indicating perfect negative correlation at -1, absence of correlation at zero, and perfect positive correlation at +1 | Correlation Coefficient |
| A symmetric bell-shaped probability distribution of infinite range | Normal |
| A probability distribution giving the probability of x, the number of successes observed during the n trials of a binomial experiment | Binomial Distribution |
| A model for finding the probability of count data resulting from any experiment, where the count x represents the number of rare events observed in a given unit time or space | Poisson |
| the sampling distribution of the t-statistic and is used whenever samples are drawn from populations possessing a bell-shaped distribution | T-Distribution |
| distribution of all possible values of the F-Statistic depending on degrees of freedom | F-Distribution |
| one that has a finite number of equally spaced and equally likely outcomes | Discrete Uniform |
| distribution of all possible values for a single variance | X^2-Distribution |
| he population of consists of N objects, consists of n objects all possible samples of n objects are equally likely to occur | Standardized Random Sample |
| size of rejection region | Alpha |
| Sample Mean | X-Bar |
| Distribution function | F(x) |
| function | f(x) |
| estimate of slope | B-Hat |
| is the standard deviation of sample means, or standard error of the mean | Xsub(i) |
| expected value of a random variable X | E(x) |
| sample correlation coefficient, based on all of the elements from a sample | r |
| estimate of y-intercept | A-Hat |
| variance of a sample | S^2 |
| coefficient of determination | R^2 |
| pooled variance | S^2p |
| level of confidence with a confidence interval | (1 - alpha) |
| Standardized score | Z |
| sample size | n |
| alternative hypothesis | H1 |
| null hypothesis | H0 |
| used to multivariate analysis of variance | Triangle-Thingy(Lambda) |
| change in a something | Other-O-Thingy(Delta) |
| simply a value by which of degrees of freedom for the test of F ratio ratio if multiplied | Y-Thingy(Epsilon) |
| type 2 error | B-Thingy(Beta) |
| standard deviation of a population | O-Thingy(Sigma) |
| correlation coefficient | P-Thingy(Rho) |
| population mean | U-Thingy(mu) |
Created by:
jmdoore4
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