# KIN 369 Lecture Notes - Interquartile Range, 5,6,7,8, Standard Deviation

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Published on 7 Nov 2013
School
Department
Course
Professor
KIN 369
1/28/13
Intro to Measurement and Evaluation
Test
o Instrument, protocol, or technique used to measure a quantity or quality of properties
or attributes of interest.
Measurement
o Process of collecting data on the property or attribute of interest
o Quantitative (Numerical based data)
o Qualitative (Non-numerical based data)
Evaluation and Assessment
o Process of interpreting the collected measurement and determining some worth or
value
o Identify deficits and decide how to improve them
Relationship between Test, Measurement and Evaluation?
o Tests are specific instruments used to collect data
o Administering the test is a process of measurement
o Evaluation requires making decisions based on data generated from tests and
measurement
Uses of Test, Measurement and Evaluation?
o Motivation
Fat loss
Training
o Diagnosis
High Cholesterol/Mono/Strep throat, etc
o Classification
Athletic categorization
o Achievement
Anywhere with reward for doing well
o Evaluation of Instruction and Programs
Surveys
o Prediction
MCAT/SAT/GRE
Submax Testing
o Research
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Statistics
What are Statistics?
o Collection, organization, analysis, interpretation and presentation of data
Why are they important?
o Analyze and Interpret Data
o Interpret Research
o Standardize Test Scores
o Determine Validity and Reliability of Tests
Measurement Scales and Displays of Data
Nominal
o Numbers represent categories
o Ex: 1=male, 2=female; 1=brown hair, 2=blond hair, 3=red hair, 4=green hair
Ordinal
o Numbers indicate rank but not spacing/intervals
o Ex: order of finish in a race
Interval
o Numbers represent equally spaced units, but there is no meaningful zero
o Ex: temperature, IQ
Ratio
o Numbers represent equally space units with an absolute zero point
o Ex: height, distance, heart rate, test scores
1/30/13
Frequency Distribution
Used to describe our data set with interval or ratio data
The best score is always on top
Includes the best through the worst scores with all intervals in between
Frequency is occurrence of each score
cf = cumulative frequency
o Simply sum the frequencies, start at the bottom and work your way up. The cf of the top
row should be equal to the total number of scores. (N = 12 for this example)
c% = cumulative percent
o Divide current cf by number of scores and convert it to a percentage. (N = 12 for this
example)
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Graphing Distributions
o Histogram
Type of bar graph
Width of bar represents interval size
Height of bar represents frequency within the interval
o Line Graph
X-axis is always some measurement of time
o Pie Chart
Displays percentages of a categories pertaining to the whole data set
How often or at which percentage each piece occurs
o Scatter Plot
Measures the relationship between two things
o Bar Graph
Comparative graph
How do you make a frequency distribution with a large range?
o Aim for approximately 5-10 intervals
o Example
Measured sit-ups
Scores ranged from 75 to 12
Far too many for intervals of 1
Break it up into segments or by set intervals
Score
Tally
f
cf
c%
9
XX
2
12
100
8
XX
2
10
83.33333
7
X
1
8
66.66667
6
XXX
3
7
58.33333
5
XXX
3
4
33.33333
4
0
1
8.333333
3
X
1
1
8.333333
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