GBDA 205 – Statistics Exam Review PDF

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GBDA 205 – Statistics Exam Review 1. 2. 3. 4. 5. 6. 7.

Introduction Univariate Analysis Univariate Analysis – Normal Distribution Bivariate Analysis – Intro/Table post Bivariate Analysis – Scatter plots/Correlation Coefficient Regression Inferential Analysis

1.Introduction Statistics is the study of the collection, analysis, interpretation, presentation and organization of data. Variables:  Nominal (Mode)  Ordinal (Mode, Median)  Interval (Mode, Median, Mean)  Ratio (Mode, Median, Mean) Nominal: either a non-number value or numbers are used to classify/categorize Ex. Employment Classification -1 for educator -2 for construction worker -3 for manufacturing worker Ordinal: numbers are used to indicate rank or order. Ex. Position within an organization -1 for president -2 for vice president -3 for plant manager -4 for department supervisor -5 for employee Interval: distances b/w consecutive integers are equal (location of zero is arbitrary) Ex. Fahrenheit, Calendar Time. Ratio: Highest level of measurement (location of zero is absolute) Ex. Weight, volume, height Two Types: 1. Categorical 2. Continuous Categorical: (discrete or qualitative variables) -The lower levels of measurement (nominal and ordinal are of the categorical type) -a categorical variable is a variable that can take on one of a limited, and fixed number of possible values.

Continuous: are quantitative variables whose numerical values can be subject to arithmetic operations. 3 Types of Analyses:  Univariate: statistics are used to sequentially summarize data regarding individual variables.  Bivariate: when statistics are used to summarize the relationship b/w 2 variable.  Multivariate: involves more than two variables. Descriptive Statistics: methods of organizing, summarizing, and presenting data in an informative way. Inferential Statistics: A decision, estimate, prediction about a population based on a sample. 2.Univariate Analysis Central Tendency: refers to where the center of a distribution of scores is (mean, median, mode) Frequency: the number of times an event or item occurs in a data set. Dispersion: refers to how spread out the actual scores are. Mean: also referred to as “the average”, adding up all individual scores of a variable and dividing by the # of scores. (can be badly affected by outliers) Mode: most frequently occurring variable attribute or response value. Median: score at the middle of a rank-ordered distribution, from smaller to larger. Dispersion: refers to how spread out a variable’s scores are in a sample. -if all cases have identical observed values = dispersion is zero -if most cases have observed values = dispersion is low -if many cases are “far away -4 common measures of dispersion:  Range  Interquartile Range  Variance & St. Dev  Index of Qualitative Variation (IQV) Range: identifies the difference b/w the highest and lowest scores in a distribution. R = max – min. (neg. = doesn’t provide much info) IQR: a quartile is the value that marks one of the divisions that breaks a series of values into four equal part. (25th percentile (Q1), 75th percentile (Q3)) IQR = Q3 – Q1: tests whether a value is in a ‘normal range’

Variance: symbolized (for samples) by s^2, is a type of measure of the deviance of scores relative to the mean. -The larger the variance, the further the individual cases are from the mean. -The smaller the variance, the closer the individual scores are to the mean. -variance is the sum of the squared deviations of each score from the mean, divided by the number of scores. Standard Deviation: (s) most commonly reported measure of dispersion, appropriate for interval and ratio variables. -If variance is 222.40, therefore St. dev. = 14.91 Frequency: (f) is the number of times the observation occurs in the data. Frequency Table:

The form of a distribution includes 3 key concepts: 1. Modality: refers to how many modes a distribution has 2. Skewness 3. Kurtosis...