Download presentation
Presentation is loading. Please wait.
Published byScott Hood Modified over 8 years ago
1
REVIEW OF BASIC STATISTICAL CONCEPTS Kerstin Palombaro PT, PhD, CAPS HSED 851 PRIVITERA CHAPTERS 1-4
2
DESCRIPTIVE STATISTICS Used to describe or summarize numeric observations Makes sense of a set of scores or observations Data are presented graphically, in tables or as summary statistics PRIVITERA CHAPTERS 1-4
3
INTERFERENTIAL STATISTICS Procedures that allow us to interpret the meaning of data PRIVITERA CHAPTERS 1-4
4
STATISTICAL TERMS RELATED TO INTERFERENTIAL STATISTICS Population-the set of individuals, items, or data of interest Sample-a selection of individuals from a given population PRIVITERA CHAPTERS 1-4
5
EXPERIMENTAL METHOD Experiment-any study that demonstrates cause Experiments manipulate an independent variable (IV) Experiments measure the effect of manipulating the IV on a dependent variable (DV) Experiments must have the following three characteristics: Randomization Manipulation Comparison PRIVITERA CHAPTERS 1-4
6
QUASI-EXPERIMENTAL METHOD Lacks, randomization, manipulation or comparison Typically has a quasi-independent variable Lacks a comparison group PRIVITERA CHAPTERS 1-4
7
CORRELATIONAL METHOD Examines the relationship between variables Can determine if a relationship exists, but cannot demonstrate cause and effect PRIVITERA CHAPTERS 1-4
8
SCALES OF MEASUREMENT Nominal scale-identifies something but provides no additional information Ordinal scale-conveys order alone Interval scale-has equidistant data points and no true zero Ratio scale-has a true zero and equidistant data points PRIVITERA CHAPTERS 1-4
9
TYPES OF DATA Continuous variable-can be measured at any place beyond a decimal point Discrete variable-measured in whole or fractional units. Quantitative variable-varies by amount and is measured numerically Qualitative variable-often represents a label and describes nonnumeric aspects of phenomena PRIVITERA CHAPTERS 1-4
10
SUMMARIZING DATA Frequency distributions summarize how often scores occur in a data set Can be grouped or ungrouped Cumulative frequency-distributes the sum of frequencies across a series of intervals Relative frequency-describes the portion of data in each interval Divide frequency by the total number of scores Relative percent-multiple relative frequency by 100 Cumulative percent-distributes the sum of relative percents across a series of intervals PRIVITERA CHAPTERS 1-4
11
GRAPHING CONTINUOUS DATA Can display frequency data graphically Histograms-graphs that distribute the intervals along the horizontal scale and list frequencies along the vertical scale Frequency polygon-dot and line graph where do it midpoint of each interval and line connects each dot Stem-and-leaf plot-common digits to a set of scores used to the left and remaining digits used to the right Useful with smaller data sets PRIVITERA CHAPTERS 1-4
12
GRAPHING DISCRETE VARIABLES Bar charts-like histograms except bars are separated from each other Pie charts-circular display to summarize relative percent of discrete and categorical data Scatterplot-display of discrete data points used to summarize the relationship between two variables PRIVITERA CHAPTERS 1-4
13
MEASURES OF CENTRAL TENDENCY Central tendency-statistical measures for locating a single score that is most representative of all of the scores in a distribution Mean-the average of a set of scores Weighted mean is the mean of a group of disproportionate scores or samples of scores Median-the middle value in a distribution of data listed in numeric order Not influenced by outliers Mode-the score the occurs most frequently in a distribution PRIVITERA CHAPTERS 1-4
14
NORMAL DISTRIBUTION Half of all scores fall above and half below the mean, median and mode Distributions can have some degree of kurtosis Distributions can be skewed Positively skewed- a group of scores falls substantially above most other scores Negatively skewed-a group of scores falls substantially below most other scores PRIVITERA CHAPTERS 1-4; Graphs from: Field, A. (2009).Everything you ever wanted to know about statistics (well, sort of). In A. Field, Discovering Statistics Using SPSS (pp. 31-60). Thousand Oaks, CA: SAGE Publications Ltd.
15
VARIABILITY The spread of scores around the mean Range-the difference between the larges value and smallest value in a data set Fractiles divide data into two or more equal parts such as percentiles PRIVITERA CHAPTERS 1-4
16
POPULATION VARIANCE Population variance-the measure of variability for the average squared distance that scores in a population deviate from the mean Deviation-the difference of each score from its mean Sum of squares-is the sum of the squared deviations of scores from their mean Variance formula for population is sum of squares divided by total population Population standard deviation is the square root of the variance Measure of variability for the average distance that scores deviate from their mean PRIVITERA CHAPTERS 1-4
17
SAMPLE VARIANCE Measures how dispersed scores are from their mean in a given sample Variance formula for sample variance is sum of squares divided by sample population minus 1 Sample standard deviation is the square root of the sample variance Measure of variability for the average distance that scores deviate from their mean PRIVITERA CHAPTERS 1-4
18
STANDARD DEVIATION Within a normal distribution… 68% of all scores lie within one standard deviation of the mean 95% of all scores lie within two standard deviations of the mean 99.7% of all scores lie within three standard deviations of the mean PRIVITERA CHAPTERS 1-4
19
REFERENCES Privitera, G.J. (2012). Introduction to Statistics. In G.J. Privitera, Statistics for the Behavioral Sciences (pp. 2-26). Thousand Oaks, CA: SAGE Publications Ltd. Privitera, G.J. (2012)Summarizing Data: Tables, Graphs, and Distributions. In G.J. Privitera, Statistics for the Behavioral Sciences (pp. 27-66). Thousand Oaks, CA: SAGE Publications Ltd. Privitera, G.J. (2012). Summarizing Data: Central Tendency. In G.J. Privitera, Statistics for the Behavioral Sciences (pp. 67-94). Thousand Oaks, CA: SAGE Publications Ltd. Privitera, G.J. (2012). Summarizing Data: Variability. In G.J. Privitera, Statistics for the Behavioral Sciences (pp. 95-125). Thousand Oaks, CA: SAGE Publications Ltd. PRIVITERA CHAPTERS 1-4
Similar presentations
© 2025 SlidePlayer.com. Inc.
All rights reserved.