Stats Exam 1

Question 1

Variable

Answer 1

A characteristic or condition that can change or take on different values

Question 2

Population

Answer 2

Set of all individuals or events of interest in a particular study

• -> Generally very large
• -> Can consist of arbitrary (random choice) categories of people, objects, and events
• -> Can include hypothetical or counterfactual events

Question 3

Parameter

Answer 3

Descriptive value for a POPULATION (greek letters)

Question 4

Statistic

Answer 4

Descriptive value for a SAMPLE

roman letters

Question 5

Descriptive Statistics

Answer 5

Methods for organization and summarizing data (ex: tables/ graphs with descriptive values i.e average score used to summarize data)

Question 6

Inferential Statistics

Answer 6

Methods for using sample data to make general conclusions (inferences) about populations

Question 7

Sampling Error

Answer 7

Discrepancy between a sample statistic and its population parameter

• -> Sample data provide only limited info about the population. So, sample stats are generally not perfect representatives of population parameters
• -> Depends critically on:
  1) amount of variability in population (ex: # of legs on cow vs. volume of milk produced)
  2) # of individuals in sample

Question 8

Discrete Variables

Answer 8

Indivisible categories (ex: class size)

Question 9

Continuous Variables

Answer 9

Infinitely divisible into whatever units a researcher may chose (ex: time and weight)
–> Time can be measured to the nearest minute, second, .5 second, etc.

Question 10

Scale of Measurement

Answer 10

Process of measuring a variable by classifying each individual into one category (nominal scale, ordinal scale, interval scale, ratio scale)

Question 11

Nominal Scale

Answer 11

Unordered set of categories identified only by name. Measurements only permit you to determine whether 2 individuals are the same of different; category of scale of measurement

Question 12

Ordinal Scale

Answer 12

Ordered set of categories. Measurements tell you direction of difference between 2 individuals, but not about magnitude of difference between neighboring categories; category of scale of measurement

Question 13

Interval Scale

Answer 13

Ordered series of equal-sized categories. Identify direction and magnitude of a difference. Zero point located arbitrarily; category of scale of measurement

Question 14

Ratio Scale

Answer 14

Interval scale where value of zero indicates none of the variable. Measurements identify direction and magnitude of differences and allow ratio comparisons of measurements; category of scale of measurement

Question 15

QUALitative (categorical) Data

Answer 15

Occur when we assign objects/ events into labeled (i.e. nominal or ordinal) groups, representing only frequencies of occurrence (ex: race, gender, yes/ no response)

Question 16

QUANTitative (measurement) Data

Answer 16

Occur when we obtain some # that describes the quantitative trait of interest
–> Can be discrete or continuous (ex: height, weight, income)

Question 17

Correlational Studies

Answer 17

Basic research design that determines if relationships exist between two variables and describe relationship
–> Observes 2 variables as they exist naturally

Question 18

Experiments (Experimental)

Answer 18

Basic research design that demonstrates cause and effect relationships between 2 variables by showing how change in the value of one variable causes changes to occur in second variable
–> One variable is manipulated to create treatment conditions. Second variable is observed and measured to obtain scores for a group of individuals in each of the treatment conditions

Question 19

Manipulated Variable

Answer 19

INDEPENDENT Variable

Question 20

Observed Variable

Answer 20

DEPENDENT Variable

Question 21

Quasi (non)- Experimental

Answer 21

• Compare groups of scores
• Do NOT use manipulated variable. Pre-existing participant variable (i.e. male/female) or a time (before/after) to differentiate groups
• Cannot demonstrate cause/ effect
• Similar to correlational research because they demonstrate/ describe relationship

Question 22

Random Sampling

Answer 22

Individuals are selected so each member of the population has an equal chance of inclusion
–> **Failure may result in statistics that dont reflect the whole population (ex: average height computed for a sample consisting of only women is unlikely to reflect the average of all adults)

Question 23

Random Assignment

Answer 23

Individuals are assigned to different groups using a random process.
–>Failure confounds (causes surprise or confusion) independent variable; Any measure difference in a dependent variable could be due solely to the assignment

Question 24

Frequency Distribution

Answer 24

An organized tabulation showing exactly how many individuals are located in each category on the scale of measurement
–> Presents an organized picture of the entire set of scores, and it shows where each individual is located relative to others in the distribution.

Question 25

Often, researchers are more interested in the relative frequency (or proportion) of individuals in each category than in the total number.

Answer 25

–Remember we usually measure statistics on samples to infer parameters of populations
–The relative frequency of a sample approximates the relative frequency of the population, whereas the raw frequency of a sample does not.

Question 26

Relative Frequency Distribution Table

Answer 26

lists the proportion (p) for each category: p = f/N. The sum of the p column should equal 1.00.
– Alternatively, the table could list the percentage of the distribution corresponding to each X value. The percentage is found by multiplying p by 100. The sum of the percentage column should equal 100%.

Question 27

Regular Frequency Distribution

Answer 27

When a frequency distribution table lists all of the individual categories (X values)

Question 28

Bin Edges (Class Intervals)

Answer 28

In a grouped table, the X column lists groups of scores, called bin edges or class intervals, rather than individual values.

• These intervals all have the same width
• The interval width selection is usually heuristic
• E.g., chosen to fit 10 intervals, chosen to fit an average of n items per interval.

Question 29

Frequency Distribution Graph

Answer 29

Score categories (X values) are listed on the X axis and the frequencies are listed on the Y axis.

Question 30

Bar Plots

Answer 30

plots showing the relationship between two variables. Usually, the height of a bar represents the value of a dependent variable when the independent variable consists of nominal or ordinal category labels.

Question 31

Histograms

Answer 31

bar plots in which the rectangles are centered above each score (or class interval) and the heights of the bars correspond to the frequencies (or relative frequencies) of the scores.
–The widths of bars should extend to the real limits of the class intervals, so that adjacent bars touch.
–Proper histograms actually represent frequencies in terms of the area rather than the height of bars, but we won’t worry about that distinction in this course

Question 32

Probability Density Curve

Answer 32

If the scores in the population are continuous variables, then the theoretical distributions describing them will often be depicted as smooth curves
–Examples of this include the normal distribution (i.e., “the bell curve”) as well as most of the test statistic distributions that we will deal with in this course (e.g., the t distribution, the F distribution, the chi-square distribution)
-The smooth curves represent the expectation that in a large population, relative frequencies should change smoothly as a function of a continuous variable.
-Related but not equivalent to relative frequencies.

Question 33

Symmetrical

Answer 33

the left side of the graph is (roughly) a mirror image of the right side (ex: bell-shaped normal distribution)

Question 34

Positively Skewed

Answer 34

the scores tend to pile up on the left side of the distribution with the tail tapering off to the right

Question 35

Negatively Skewed

Answer 35

the scores tend to pile up on the right side and the tail points to the left

Question 36

Unimodal

Answer 36

Has one peak

Question 37

Bimodal (multimodal)

Answer 37

distribution has two (multiple) peaks

Question 38

Mean

Answer 38

The mean is the most commonly used measure of central tendency.
The population mean is denoted by:
-The sample mean is denoted by:
-Computation of the mean requires scores that are numerical values measured on an interval or ratio scale.

Question 39

Median

Answer 39

If the scores in a distribution are listed in order from smallest to largest, the median is defined as the midpoint of the list.
-The median divides the scores so that 50% of the scores in the distribution have values that are equal to or less than the median.

Question 40

Mode

Answer 40

Most frequently occurring category or score in the distribution

Question 41

Percentile Rank

Answer 41

the percentage of individuals with scores equal to or less than that X value

Question 42

Percentile

Answer 42

When an X value is described by its rank

Question 43

Central Tendency

Answer 43

A statistical measure that determines a single value that accurately describes the center of the distribution and represents the entire distribution of scores.
-The goal of central tendency is to identify the single value that is the best representative for the entire set of data