MBA 621 EXAM 1 QUESTIONS ANSWERED CORRECTLY LATEST UPDATE 2026

MBA 621 EXAM 1 QUESTIONS ANSWERED CORRECTLY LATEST UPDATE 2026 Why Statistics and Why Excel/SPSS? - Answers •Excel/SPSS are the most popular and powerful analytic tool. •It is a great skill for the workplace. •Required for statistics in future. History of Statistics - Answers •Descriptive statistics began in the 17th century. -The first set of data pertaining to populations was collected. • Scientists developed specific tools to answer questions. •Personal computers, spreadsheets, and software applications have increased the use of statistical techniques for everyone. •Powerful personal computers, the internet, and artificial intelligence apps have been both good and bad for statistics. Statistics - Answers describes a set of quantitative tools and techniques used to describe, organize, and interpret information or data Descriptive statistics - Answers used to organize and describe the characteristics of a collection of data •The collection is called a data set or just data. Average - Answers the one value that best represents an entire group of scores. •They are also called measures of central tendency and include the mean, median, and mode. Mean - Answers the sum of all the values in a group, divided by the number of values in that group -very sensitive to extreme scores (outliers) -mean is sometimes represented by the letter M Median - Answers the midpoint in a distribution or set of scores -not sensitive to extreme scores (outliers) -percentile ranks are used to define the percentage of cases equal to or below a certain point in a distribution or set of scores Mode - Answers the value that occurs most frequently -The mode is the most general and least precise measure of central tendency Inferential Statistics - Answers when you use information about a sample to make guesses about a population •A smaller group of data is called a sample, which is a portion or a subset of a population. •The population is the large group of people/things you want to describe. Levels of measurement - Answers types of data that include the mode, median, and mean and are in order of how much information is in the distribution Measurement - Answers the assignment of values to outcomes following a set of rules. •Outcomes are a group of scores that provide different amounts of information about things and concepts. 4 levels of measurement - Answers 1. Nominal 2. Ordinal 3. Interval 4. Ratio Compare/Contrast 4 levels of measurement - Answers •If your scores just represent categories, use the mode. •If your scores are spread out, but not evenly spaced, use the median. •If your scores are spread out and evenly spaced, use the mean. NOMINAL level of measurement - Answers describes situations where the numbers are used only as names for different categories. •One category isn't more or less than another. •Example: which country you are from. If you are from Canada, we might code that as a 1 in our data. Some other country would get another number. ORDINAL level of measurement - Answers the things being measured are in some meaningful order. •We know that one number is "better" than another, but not by how much. •Example: a rank of candidates for a job. If we know that Russ is ranked 1, Marquis is ranked 2, and Hannah is ranked 3, then this is an ordinal arrangement. INTERVAL level of measurement - Answers about the distances or intervals between any two adjacent scores anywhere along the scale. •If all intervals are "equal" along the range of possible scores, we call that interval level. •Example: Think of a Celsius thermometer, the difference between 48 degrees and 47 degrees is one degree of heat, and the difference between 34 degrees and 33 degrees is also one degree of heat. RATIO level of measurement - Answers characterized by the presence of an absolute zero on the scale. •On ratio-level scales, there is nothing less than zero. •It's the only level where talking about ratios or percentages makes sense. Variability - Answers reflects how much scores differ from one another •Three measures of variability are used to reflect the degree of variability, spread, or dispersion in a group of scores. (range, the standard deviation, and the variance) •Sets of data can have the same mean but have different amounts of variability. Range - Answers the distance of the biggest score from the smallest score •Formula for the range: r = l -s •The range is computed by subtracting the lowest score in a distribution from the highest score in the distribution. Variance - Answers the average amount of distance of each score from the mean. How to find: •Take each score and subtract the mean from it to create a difference score. •Square each difference score before adding them up. •Calculate the mean of those distance scores. Standard Deviation - Answers (SD or s) represents the average amount of variability in a set of scores -the larger the standard deviation: •The larger the average distance each data point is from the mean of the distribution. •The more variety there is in the set of scores. Frequency Distribution - Answers This is a method of tallying and representing how often certain scores occur in a set of scores. •"SCALE" refers to the proportional relationship between the horizontal and vertical axes. •In the creation of a frequency distribution, scores are usually grouped into class INTERVALS, or ranges of numbers. Histograms - Answers graphs of frequency distributions where the frequencies are represented by bars Line Charts - Answers should be used when you want to show change; this sort of graph is often used when the x-axis represents time Pie Charts - Answers should be used when you want to show the proportion or percentage of people or things that are in each category of a nominal-level variable Correlation Coefficient - Answers a number that reflects the relationship or association between two variables •The value of this descriptive statistic ranges between −1.00 and +1.00. Pearson product-moment correlation - Answers used when both variables are at the interval level of measurement. •It is represented by r with a subscript representing the variables that are being correlated. Positive Correlation - Answers If variables change in the same direction Negative Correlation - Answers If variables change in different directions Absolute Value VS Correlation Coefficient - Answers •The ABSOLUTE VALUE of the coefficient reflects the strength of the correlation. •The CORRELATION COEFFICIENT reflects the amount of variability that is shared between two variables and their commonalities. Scatterplot - Answers A plot that puts a dot where the pairs of score are with the two variables as the X and Y axes. •The general shape of the collection of data points indicates if the correlation is direct (positive) or indirect (negative). •Most scatterplots do not create a perfectly straight line. Correlation matrix - Answers should be used when you have more than two variables and you want to see correlations among all pairs of variables. •For each pair of variables, there is a correlation coefficient. •Sometimes the matrix creates a mirror image of itself. Rule of Thumb Method - Answers 0.5 to 1.0 -- Strong 0.4 -- Moderate to strong 0.3 -- Moderate 0.2 -- Weak to moderate 0-0.1 -- Weak to no relationship Effect Size - Answers an index of the strength of the relationship among variables Coefficient of determination - Answers the percentage of variance in one variable that is accounted for by the variance in the other variable Coefficient of Alienation - Answers the amount of variance in Y not explained by X, and vice versa True or False: A relationship between two variables means one variable affects the other - Answers FALSE; Correlations express the association that exists between two or more variables; they do not prove causality. Partial Correlation - Answers the correlation you would get between two variables if the overlap of a third variable is removed Controlling - Answers CONTROLLING for a third variable means calculating the correlation between two variables if their correlation with a third variable is zero. Mediating Variable - Answers comes between two variables of interest and explains the apparent relationship Confounding Variable - Answers affects the A and C variables directly, but it doesn't come in the middle of a cause-and-effect path Reliability - Answers the degree to which scores are random as opposed to what a person would typically get Validity - Answers the degree to which scores represent the concept that a researcher thinks it does Dependent Variable - Answers outcome variable; reveals if a change has occurred from the treatment/intervention that has taken place Independent Variable - Answers the treatment/intervention Classical Test Theory - Answers the conceptual framework behind our notion of reliability Observed Score - Answers what you actually get on a test True Score - Answers the typical score you would get if you took the same test an infinite number of times and averaged all your scores What is the difference between an observed score and true score? - Answers Error Error Score - Answers the difference between the observed score and true score due to random error •Reducing these random errors increases reliability. Test-Retest Reliability - Answers used to examine if a test produces similar scores over time •It is determined by administering a test and the readministering the same test at a different time. Internal Consistency Reliability - Answers used to find if the items on a test correlate with one another strongly enough to assume they measure the same thing and can be added into a total score •The total score is the combination of many observations. •Adding observations of the same thing should decrease randomness and increase reliability. Cronbach's alpha - Answers a special index of reliability that reflects internal consistency •The more strongly individual item scores relate to each other, the higher the value of Cronbach's alpha. •The higher the value of Cronbach's alpha, the more confidence you can have that this test is internally consistent and correlates well inside itself. Interrater Reliability - Answers an estimate that tells you how much two different people (raters) agree on which score to assign •The more similar the raters' ratings are, the higher the level of interrater agreement and interrater reliability will be •Formula: Number of agreements/Number of opportunities to agree Interpreting Reliability Coefficients - Answers With reliability coefficients, we want reliability estimates to be: •Positive and not negative. •As close to 1.0 as possible. •For most types of reliability, we want coefficients to be at least 0.70 or higher. If you can't establish reliability then what? - Answers •Ensure that instructions are standardized and clear across all settings in which the test is administered. •Increase the number of items or observations on a test. •Delete unclear items. •For an achievement test, ensure that questions aren't too hard or too easy. •Minimize effects of external events on test performance. •The first step in creating an instrument with sound psychometric properties is to establish its reliability. Valid Test - Answers measures what it is supposed to and works well for its intended purpose -Remember that validity, put simply, is the characteristic of an instrument or measurement tool that does what it says it does.