fear free stats! what you need to know to be successful on the ap test
TRANSCRIPT
Fear Free Stats!
What you need to know to be successful on the AP Test.
Intro to STATS
Statistics (Stats) can be used as a tool to help demystify research
data. Examples:
Election polls Market research Exercise regimes Surveys Etc.
Definition of Statistics
A means of organizing and analyzing data (numbers) systematically so that they have meaning.
Types
Descriptive Stats- Organize data so that we can
communicate about that data
Inferential Stats- Answers the question, “What can we
infer about the population from data gathered from the sample?”
Generalizability
Measurement Scales
Nominal Scale
Ordinal Scale
Interval Scale
Ratio Scale
Looking at data in a meaningful way
EXAMPLE These numbers have little meaning
until they are organized.
91 92 87 99 83 84 82 93 89 91 85 94 91 98 90
Frequency distribution
Frequency distribution- an organized list that enables us to see clusters or patterns in data.
99 – 1 98 – 1 97 – 0 96 – 0 95 – 0 94 – 1 93 – 1 92 – 1 91 – 3 and so on.
Grouped Frequency of same scores
95-99 2 90-94 7 85-89 3 80-84 3 N=15 The width of the intervals in
grouped frequency tables must be equal. There should be no overlap.
Moving on to Graphs
These allow us to quickly summarize the data collected.
In a glance, we can attain some level of meaning from the numbers.
Pie Charts
A circle within which all of the data points or numbers are contained in the form of percentages.
Bar Graphs
A common method for representing nominal data where the height of the bars indicates percentage or frequency of each category
Frequency Polygons A line graph that has the same vertical
and horizontal labels as the histogram Each score’s frequency of occurrence
is marked with a point on the graph, when all points are connected with a line
The Frequency Polygon
Useful in showing the asymmetry in distribution of ordinal, interval and ratio data.
This asymmetry is referred to as SKEW.
Positive and Negative SKEW
If there is a clustering of data on the high end, then the skew is NEGATIVE because skewness is always indicative of the “tail” or low end of the graph as indicated by low frequency of occurrence.
A POSITIVE skew would be indicated by high frequency of low end data points with a few data points at the high end
The Tail Tells the Tale
The line of the frequency polygon “tails off” to include these low frequency ends or SKEWNESS
Line Graphs
Indicate change that occurs during an experiment.
Shows the change in relationship between IV and DV
IV always on the vertical axis and DV on horizontal axis
Graphs don’t lie
But different representations will provide a different visual that can be deceptive.
Descriptive Statistics
Measures of central tendency- these numbers attempt to describe the “typical” or “average” score in a distribution.
What are the measures of central tendency?
Mode
The most frequently occurring score in a set of scores.
When two different scores occur most frequently it is referred to as bimodal distribution.
Example?
Median
The score that falls in the middle when the scores are ranked in ascending or descending order.
This is the best indicator of central tendency when there is a skew because the median is unaffected by extreme scores.
If N is odd, then the median will be a whole number, if N is even, the position will be midway between the two values in the set.
Mean
The mathematical average of a set of scores
The mean is always pulled in the direction of extreme scores (pulled toward the skew) of the distribution.
Examples?
Examples
SAMPLE TEMPERATURESWeek One: Week Two: 71 74 76 79 98 70 74 76 77 78
CALCULATE:MEAN OF WEEK ONE MEAN OF WEEK TWOMEDIAN OF WEEK ONE MEDIAN OF WEEK TWOMODE OF WEEK ONE MODE OF WEEK TWO
MEAN OF BOTH WEEKS COMBINEDMEDIAN OF BOTH WEEKS COMBINEDMODE OF BOTH WEEKS COMBINED
MEASURE OF CENTRAL TENDENCY CAN BE MISLEADING
Suppose your mother wants you to attend a family reunion on Sunday.
Everyone in the family protests! Your mother attempts to
separately convince each family member that it will not be so bad.
Mom’s story
Mom tells your younger sister that the average age of the gathering is 10 years old.
She tells you the average age is 18. She tells dad that the average age is 36. Now each family member feels better
about spending the day at the family reunion.
Did Mom lie?
The AttendeesInformation
AGES NAME AND RELATION
3 Cousin Susie 7 Cousin Sammy 10 Twin Shanda 10 Twin Wanda 15 Cousin Marty 17 Cousin Juan 18 Cousin Pat 44 Aunt Harriet 49 Uncle Stewart 58 Aunt Rose 59 Uncle don 82 Grandma Faye 96 Great Aunt Lucille
Answer me this
What is the median?What is the mode?What is the mean?
Did Mom “lie”?
Answers
What is the median? 18
What is the mode? 10
What is the mean? 36
Did Mom “lie”? Not really. . .
Measures of Variability
Measures of variability indicate how much spread or variability there is in a distribution.
If you collected the ages of all students in the 11th grade, there would be little variability.
If you collected the shoe sizes of all students in the 11th grade, there would be greater variability.
Range
The range is the difference between the lowest and highest score in the data set.
The range of scores can be significantly increased with a single outlying score.
Example
Class One: 94, 92, 85, 81, 80, 73, 62
Range=32
Class Two: 85, 83, 82, 81, 80, 79, 77
Range= 8
Variance
This is a measure of how different the scores are from each other.
The difference between the scores is measured by the distance of each score from the mean of all the scores.
FORMULA: Variance= Standard Deviation squared
SD2
Standard Deviation
This measure of variability is also based on how different scores are from each other.
There are computer programs and calculators used for this data.
FORMULA: The Standard Deviation is the square root of
the variance
Normal Distribution
The normal curve is a theoretical or hypothetical frequency curve.
Most frequency curves are not symmetrical (remember skew)
Normal distribution is displayed on a graph with a “bell” shaped curve.
Bell Curve
%%%%%%%%%%% Must be memorized
Correlations
Correlation describes the relationship between two variables
How is studying related to grades?
How is playing video games related to grades?
Positive Correlation
Indicates a direct relationship between variables
Variables move in the same direction An increase of one variable is
accompanied by an increase in another variable
A decrease in one variable is accompanied by a decrease in another variable
Negative Correlation
Indicates an inverse relationship between variables
An increase in one variable is accompanied by a decrease in another variable, or vice versa.
Correlation coefficients
Correlations are measured with numbers ranging from -1.0 to +1.0.
These numbers are called correlation coefficients.
Correlation Coefficient
As the correlation coefficient moves closer to +1.0, the coefficient shows an increasing positive correlation.
As the correlation coefficient moves closer to -1.0, the stronger the negative correlation.
A zero could indicate no correlation exists between variables
+1.0 and -1.0 indicate a perfect correlation
Continued
Which is a stronger correlation? -.85 or +.62 +.45 or -.23 -.70 or +.70
The absolute value of the number indicates the strength of the correlation.
But…
Correlation does not imply causation!
Correlational Studies
An often used research design.
May not have IV and DV, may be variable one and two.
Examples?
Scatter Plots
A visual representation of correlations
The x variable is on the horizontal axis and the y variable is on the vertical axis
Scatter Plot
Scatter Plot
Scatter Plot
Inferential Statistics
Help us determine if one variable has an effect on another variable.
Helps us determine if the difference between variables is significant enough to infer (for credit on an AP Exam, you cannot use the term to define the term) that the difference was due to the variables, rather than chance.
Statistical Significance
Are the results of research strong enough to indicate a relationship (correlation)? Would you publish the results?
Researchers commonly use two inferential tests to measure significance
T-test ANOVA
Are You Free of Fear?????
Statistics is an important aspect of research design in psychology.
In college you will take an entire course in the Statistics of Psychology.
If you have a grasp of what was presented today, you will be successful on the AP Exam.
STATS Activity
Dice and the Bell Curve (Rob McEntarffer) In this lesson, students use a simple method of
gathering and plotting data. Students will discover that the data falls along a bell (normal) curve.
You and a partner or two get a pair of dice.
Roll the dice, add the results of each die and record the sum in some organized manner.
Roll the dice 50 times.