KIN 4310: EXAM 1
90 Cards in this Set
| Front | Back |
|---|---|
|
Measurement
|
The act of measuring or the process of being measured.
The act of collection of information upon which a decision is based
|
|
Evaluation
|
To examine and judge carefully; appraise.
The use of measurement in making decisions
|
|
Prediction
|
The act of predicting (by reasoning about the future)
|
|
Law
|
Concise statement of fact that has been proven time and time again, and is generally accepted as true and universal, like Newton's Law of Gravity.
|
|
Theory
|
Set of principles devised to explain a phenomena, especially one that has been repeatedly tested and can be used to make predictions about natural phenomena
|
|
Hypothesis
|
Attempt to explain some basic observations before precise data has been rigorously collected and analyzed
Educated guess that may or may not be true
|
|
Data
|
Observations that can be represented by numbers, words or symbols
The basis of statistical analyses
|
|
Quantitative Data
|
Deals with numbers
Can be measured
|
|
Qualitative
|
Deals with descriptions
Can be observed
|
|
Statistics
|
A collection of methods for planning experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions based on the data.
Usually refers to data represented by numbers or symbols
|
|
Population
|
Complete collection of all elements (scores, people, measurements, and so on) to be studied--in the sense that it includes all subjects to be studied
|
|
Census
|
The collection of data from every member of the population
|
|
Sample
|
A sub-collection of elements drawn from a population
|
|
Statistic
|
A numerical measurement describing some characteristic of a sample
|
|
Parameter
|
A numerical measurement describing some characteristic of a population
|
|
Sampling Error
|
The difference between a statistic and the associated parameter
|
|
Nonsampling Error
|
Sample data that are incorrectly collected, recorded, or analyzed (such as by selecting a biased sample, using a defective instrument, or recording the data incorrectly)
|
|
Types of Statistics
|
Descriptive and inferential
|
|
Descriptive Statistics
|
Summarize or describe characteristics of a known set of data
|
|
Inferential Statistics
|
Use sample data to make inferences (or conclusions and predictions) about a sample
Correlational or experimental designs
|
|
Important Characteristics of Data
|
Center, Variability, Distribution and Outliers
|
|
Center
|
A representative or average value that indicates where the middle of the data set is located
|
|
Variability
|
A measure of the amount that the values vary among themselves.
|
|
Distribution
|
The nature or shape of the distribution of data (such as bell-shaped, uniform, or skewed)
|
|
Outliers
|
Sample values that lie very far away from the vast majority of other sample values.
|
|
Measure of Central Tendency
|
A value at the center or middle of a data set (Mean, Median and Mode)
|
|
Mode
|
The value that occurs most frequently
Not always unique
Good for nominal level of measurement-use when data is categorical
|
|
Median
|
Middle value when the original data values are arranged in order of increasing (or decreasing) magnitude
Use when data is skewed
|
|
Mean
|
The measure of center obtained by adding the values and dividing the total by the number of values
Use otherwise
|
|
x, n, N
|
Is the variable usually used to represent the individual data values.
Represents the number of values in a sample.
Represents the number of values in a population.
|
|
Measures of Variability
|
Range, Standard Deviation, Variance
|
|
Range
|
Maximum value - minimum value
|
|
Standard Deviation
|
A measure of variation of values from the mean
|
|
Variance
|
Standard deviation squared
|
|
Methodological Approaches
|
Descriptive, Correlational, Experimental
|
|
Descriptive Study
|
Most common type of study
Observe and measure specific characteristics without attempting to modify the subjects that are being studied
|
|
Correlational Study
|
Used commonly in health science studies
Describes something in relation to something else
Observations are not manipulated, merely related to each other
There is no causation
|
|
Experimental Study
|
Hard to do well
Apply some treatment and then observe its effects on the subjects
|
|
Correlation
|
A relationship between two variables.
A correlation equation can be generated for predicting the value of one variable given the value of the other variable.
Averages suppress individual variation and may inflate the correlation coefficient.
There may be some relationship between x and…
|
|
Linear Correlational Coefficient
|
A numerical measure of the strength of the relationship between two variables representing quantitative data
Represents direction and strength
=0: no correlation
=1: perfect positive correlation
=-1: perfect negative correlation
|
|
Coefficient of Determination
|
The value of r2 is the proportion of the variation in y that is explained by the linear relationship between x and y
|
|
Causation
|
It is wrong to conclude that correlation implies causality
|
|
Methods of Sampling
|
Random, Systematic, Convenience, Stratified, Cluster
|
|
Random Sampling
|
Members of the population are selected in such a way that each individual member has an equal chance of being selected
|
|
Systematic Sampling
|
Select some starting point and then select every Nth element in the population
|
|
Convenience Sampling
|
Data or results that are easy to get
|
|
Stratified Sampling
|
Subdivide the population into at least two different subgroups, then draw a sample from each subgroup
|
|
Cluster Sampling
|
Divide the population into sections (or clusters); randomly select some of those clusters; choose all members from selected clusters
|
|
Cross Sectional Study
|
Data are observed, measured, and collected at one point in time.
|
|
Retrospective Study
|
Data are collected from the past by going back in time
|
|
Prospective Study
|
Data are collected in the future from groups (called cohorts) sharing common factors
|
|
Confounding
|
Occurs in an experiment when the experimenter is not able to distinguish between the effects of different factors
|
|
Strategies to Avoid Confounding
|
Blinding, Matching, Randomized Controlled Trial
|
|
Blinding
|
Participant does not know whether he or she is receiving a treatment or placebo
|
|
Matching
|
Select participants with similar characteristics
|
|
Randomized Controlled Trial
|
Randomly assign participants to each experimental group
Gold standard of scientific research
|
|
Frequency Distribution
|
Lists data values (either individually or by groups of intervals), along with their corresponding frequencies or counts
The interval is called a class or bin
Helpful for summarizing large data sets
Most often illustrated in bar graphs
|
|
Histogram
|
Type of graph that portrays the nature of a data distribution
|
|
Symmetric Data
|
Distribution of data is symmetric if the left half of its histogram is roughly a mirror image of its right half
|
|
Skewed Data
|
Distribution of data is skewed if it is not symmetric and if it extends more to one side than the other
|
|
Negative Skew
|
Long tail goes to left
|
|
Positive Skew
|
Long tail goes right
|
|
Frequency Polygon
|
Uses line segments connected to points directly above class midpoint values
|
|
Dot Plot
|
A graph in which each data value is plotted as a point (or dot) along a scale of values
|
|
Stemplot (Stem-and-Leaf)
|
Represents data by separating each value into two parts: the stem (such as the leftmost digit) and the leaf (such as the rightmost digit)
|
|
Pareto Chart
|
A bar graph for qualitative data, with the bars arranged in order according to frequencies
|
|
Pie Chart
|
A graph depicting qualitative data as slices of a pie
|
|
Scatter Plot
|
A plot of paired (x,y) data with a horizontal x-axis and a vertical y-axis
|
|
Box Plot
|
Boxes represent quartiles; Range shown by whiskers; extreme values shown as dots
|
|
Time Series Graph
|
A graph of data that have been collected at different points in time
|
|
Misuses of Statistics
|
Refusals, Correlation & Causality, Self Interest Study, Precise Numbers, Partial Pictures, Deliberate Distortions, Bad Samples, Small Samples, Misleading Graphs, Pictographs, Distorted Percentages, Loaded Questions, Order of Questions
|
|
Voluntary Response Sample
|
Respondents decide whether to be included
Valid conclusions can be made only about the specific group of people who agree to participate
|
|
Measurement
|
Consists of rules for assigning numbers to (objects) in such a way as to represent quantities of attributes.
Most measurement is indirect.
|
|
Classical Test Theory
|
O= T + E
|
|
Observed Score
|
The actual score on a test that results from your measurement
|
|
True Score
|
The actual amount of the attribute you want to measure
|
|
Error score
|
Anything you did not intend to measure that affected the score
|
|
Systematic Error
|
Recurs on repeated measurements and affects scores predictably
|
|
Nonsystematic Error
|
Unpredictable and varies with every measurement
|
|
Levels of Measurement
|
Nominal, Ordinal, Interval, Ratio
|
|
Nominal Scales
|
Mutually exclusive, unordered categories
Ex. gender, country of origin
|
|
Ordinal Scales
|
Characteristics that can be put in order, but there is no consistent difference between adjacent scores
Ex. rank, olympic medal color
|
|
Interval Scales
|
Variables refer to quantities of units on a continuum
Distance between variables is meaningful
Ex. Temperature, IQ
|
|
Ratio Scales
|
Has an absolute zero
Ex. annual salary, body mass percentage
|
|
Reliability
|
The degree to which scores are:
Free from errors of measurement
Consistent, or stable across a variety of conditions
Reliability is necessary, but not sufficient for validity
|
|
Types of Reliability
|
Test-retest reliability, Interrater reliability, Internal consistency reliability, Parallel forms reliability
|
|
Test-Retest Reliability
|
Correlation of scores on a test given at two separate times (ex. One PT assesses each patients twice in 48 hours)
|
|
Interrater Reliability
|
Correlation of scores measured by two different observers or raters
|
|
Internal Consistency Reliability
|
A function of the relationship between items on a scale and the number of items (ex. attorney is concerned that the three components of the field sobriety test do not assess the same thing)
|
|
Parallel Forms Reliability
|
Correlation of scores between two different versions of a test (ex. GRE)
|
KIN 4310: Statistics