BUAD 231 - Midterm Study Guide

Statistics

Art and science dealing with the collection, preparation, analysis, interpretation, and presentation of data

Data

Compilations of facts, figures or other contents

Population

All items of interest

Sample

A subset of the population that data is collected on

Descriptive statistics

Summary of important aspects of a data set

Inferential Statistics

Drawing conclusions about a population based on a sample

Element

Entities on which data are collected

Variable

Characteristic of the elements

Observation

Set of measurements obtained for a particular element

Cross sectional data

Data collected at the same or approximately the same point in time for multiple elements

Time Series Data

Refers to data collected over several time periods focusing on certain groups of people, events, or objects

Structured Data

Data conformed to row-column format

Unstructured data

Data not conformed to row-column format

Quantitative Data

Numerical values indicating how much or how many

Categorical data

Labels to identify categories of items

Frequency distribution

How often different values of a variable occur

Bar chart

Graphical display to depict qualitative data. One axis is labels for the classes, the other is frequency or variation of frequency

Pareto Diagram

Bar chart with bars sorted in descending height order

Pie chart

Graphical display for showing relative frequency for categorical data

Cumulative Frequency Distribution

Number of items with values less than or equal to upper limit of each class

Dot Plot

Horizontal axis shows range of quantitative data values, each value represented by a dot placed above the axis

Histogram

Quantitative variable of interest placed on horizontal axis, no separation, other than that just like a bar chart

Stem-and-Leaf Display

Rank order and shape of distribution. Basically a sideways histogram showing data values.

Crosstabulation

Tabular summary of data for two variables to show relationship between variables

Scatter diagram

Graphical presentation of the relationship between quantitative variables

Trendline

Approximation of the relationship between two quantitative variables

Side-by-side bar chart or stacked bar chart

Graphical display for depicting multiple bar charts and comparing two variables 

Sample statistics

Measures computed for data from a sample

Parameters

Measures computed for data from a population

Mean

Provides a measure of central location

Median

Value in the middle when the data items are arranged in ascending order. If data set has extreme values, median is preferred measure of center

Trimmed Mean

Deleting a percentage of smallest and largest values from a data set and computing the mean of remaining values.

Mode

Value that occurs with greatest frequency

Weighted Mean

Mean is computed by giving each observation a weight that reflects relative importance

Geometric Mean

Finding the nth root of the product of n values

Percentile

Provides information about how the data are spread over the interval from the smallest value to the largest value

Range

Data set is the difference between the largest and smallest data value

Variance

Measure of variability that uses all data based on difference between value of each observation and mean

Standard Deviation

Positive square root of variance, measured in the same units as the data

Coefficient of Variation

Indicates how large the standard deviation is in relation to the mean

Skewness

Important numerical measure of the shape of a distribution

Z-score

Standardized value, number of standard deviations from the mean

Finite Population

A population where the number of items is set

Infinite Population

Population with no set upper limit on the number of items

Point Estimation

Using data from the sample to compute a value of sample statistic that serves as an estimate of the population parameter

Target Population

Population we want to make inferences about

Sampled Population

Population from which the sample is taken

Central Limit Theorem

In selecting random samples of size n from a population, the sampling distribution of the sample mean can be approximated by a normal distribution as the sample size becomes large