OT 667

1
OT 667

• Descriptive Statistics

2
Why do we measure things?
3
In order to

• Describe
• Compare
• Categorize levels of function
• Document improvement
• Demonstrate efficacy

4
One way to manipulate numbers

• Statistics (measures of a sample) or
• Parameters (measures of a population) can
• be used to organize, summarize and
• analyze measurements to give information

5
Levels of Measurement

• Nominal categorical variables (gender, hair
  color, ethnicity)
• Ordinal rank order of observation (muscle
  testing, pain levels, military rank)
• Interval equal intervals between scores but no
  true zero (calendar years, degrees centigrade or
  Fahrenheit)
• Ratio true equal intervals between units,
  measured from true zero (distance, age, time,
  weight, strength, blood pressure, degrees Celsius)

6
Kinds of Statistics

• Descriptive statistics the use of measures to
  describe aspects of a sample or population
• Inferential statistics the process of drawing
  inferences/making judgments about samples that
  are generalized to the larger population

7
Descriptive Statistics

• Measures of central tendency
• Measures of variability
• Relationship to the normal curve

8
Measures of Central Tendency

• Mode - the most frequently occurring score in a
  distribution
• Median the exact middle score in a distribution
• Mean the average score of a distribution

9
Levels of Measurement and Measures of Central
Tendency

• Mode Median Mean
• Nominal Ordinal Interval
• Ordinal Interval Ratio
• Interval Ratio
• Ratio

10
(No Transcript)
11
(No Transcript)
12
(No Transcript)
13
(No Transcript)
14
(No Transcript)
15
Measures of Variability

• Range the difference between the highest and
  lowest scores in a distribution
• Variance the mean of the square deviation
  scores
• Standard Deviation the square root of the
  variance most consistently used variation score

16
What ARE correlation coefficients?What does
correlation mean?When would I use correlation
procedures?
17
Correlation coefficients are measures of
relationship.
18
measurement of relationship as defined by
the magnitude of the relationship the
direction of the relationship
19
Venn Diagrams..
20
The nature of relationships

• Correlation coefficients describe linear
  relationships (ROM/muscle testing)
• Curvilinear relationships (gross motor skills
  over the lifespan) are not well described by
  correlations

21
Meaning of correlation

• Two variables have a relationship
• The nature of the relationship is unclear
• A relationship DOES NOT imply causality
• Further investigation of the relationship may
  reveal it is spurious
• Correlations are based on similar levels of
  variability (covariance) between variables

22
Which means.

• If you have two variables and measure them in a
  population and both levels are high, the
  correlation will be low
• This is called restriction of the range
• The formula for calculating correlation
  coefficients is based on the variability of the
  scores on the different variables, so without
  deviation, the coefficient will be low

23
Magnitude and Direction

• Correlations are within a range of 1 to 1
• Variables that are positively correlated are
  highly related
• Variables that are negatively correlated are
  highly unrelated.

24
Correlation Coefficients

• Pearsons used with continuous variables on an
  interval or ratio level
• Spearmans used with ordinal level data
• Phi coefficient used with 2 dichotomous
  variables
• Point and rank biserial coefficents used with
  one dichotomous variable and one continuous
  variable

25
(No Transcript)