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Statistics. Descriptive Statistics Inferential Statistics. Descriptive statistics Used to describe a set of data Inferential statistics Used to draw inferences about a population based on data obtained from a sample. Parameter Statistic. Scales of Measurement.

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slide2

Descriptive Statistics

Inferential Statistics

slide3

Descriptive statistics

Used to describe a set of data

Inferential statistics

Used to draw inferences about a population based on data obtained from a sample.

Parameter

Statistic

scales of measurement
Scales of Measurement

Nominal scales (Categorical data)

Ordinal scales

Interval scales

Ratio scales

distributions
Distributions

IQ Scores

113, 117, 84, 103, 105, 108, 115, 126, 103, 112, 106, 111, 113, 90, 107, 76, 109, 97, 103, 97, 89, 101, 93, 99, 115, 94, 94, 94, 108, 97, 95, 87, 107, 97, 88, 99, 97, 82, 112, 91, 107, 93, 83, 99, 100, 92, 102, 93, 100, 83, 125, 96, 84, 113, 113, 96, 97, 88, 100, 95, 86, 77, 80, 125, 110, 114, 121, 102, 90, 103, 91, 103, 109, 104, 79, 100, 85, 76, 115, 105, 95, 88, 93, 111, 107, 108, 98, 84, 123, 107, 118, 93, 101, 92, 99, 92, 136, 121, 97, 101, 102, 114, 103, 81, 71, 104, 85, 106, 120, 108, 112, 131, 94, 104, 121, 123, 91, 103, 93, 102

N = 120

slide6

IQ Scores - Ranked

71, 76, 76, 77, 79, 80, 81, 82, 83, 83, 84, 84, 84, 85, 85, 86, 87, 88, 88, 88, 89, 90, 90, 91, 91, 91, 92, 92, 92, 93, 93, 93, 93, 93, 93, 94, 94, 94, 94, 95, 95, 95, 96, 96, 97, 97, 97, 97, 97, 97, 97, 98, 99, 99, 99, 99, 100, 100, 100, 100, 101, 101, 101, 102, 102, 102, 102, 103, 103, 103, 103, 103, 103, 103, 104, 104, 104, 105, 105, 106, 106, 107, 107, 107, 107, 107, 108, 108, 108, 108, 109, 109, 110, 111, 111, 112, 112, 112, 113, 113, 113, 113, 114, 114, 115, 115, 115, 117, 118, 120, 121, 121, 121, 123, 123, 125, 125, 126, 131, 136

N = 120

slide7

Frequency distribution of IQ scores

Cumulative

Value

Frequency

Percent

Percent

71

.8

1

.8

76

2

1.7

2.5

77

1

.8

3.3

79

.8

1

4.2

80

.8

5.0

1

81

1

.8

5.8

82

1

.8

6.7

83

1.7

2

8.3

84

3

2.5

10.8

85

2

1.7

12.5

86

1

.8

13.3

87

1

.8

14.2

88

3

2.5

16.7

89

1

.8

17.5

90

2

1.7

19.2

91

3

2.5

21.7

.

.

.

.

136

1

.8

100.0

Total

120

100

slide8

Grouped Frequency Distribution of IQ scores

Mid-

Cumulative

Value

F

Percent

point

Percent

72

1

.8

.8

70 - 74

4

3

.3

4

75 -79

77

.2

82

8

6

.6

10

.8

80 - 84

8

6

.6

85 - 89

87

17

.5

92

18

15

.0

32

.5

90 - 95

95 - 99

97

17

14

.2

46

.7

102

21

17

.5

64

.2

100 -104

107

15

12

.5

76

.7

105 - 109

12

10

.0

86

.7

110 - 114

112

117

5

4

.2

90

.8

115 - 119

6

5

.0

95

.8

120 - 124

122

127

3

2

.5

98

.3

125 - 129

1

.8

.2

130 - 134

132

99

137

1

.8

100

.0

135 - 139

N

120

measures of central tendency
Measures of Central Tendency

Mode

The most common score

slide14

Grouped Frequency Distribution of IQ scores

Mid-

Cumulative

Value

F

Percent

point

Percent

70 - 74

72

1

.8

.8

77

4

3

.3

4

.2

75 -79

8

6

.6

80 - 84

82

10

.8

8

6

.6

85 - 89

87

17

.5

92

18

15

.0

32

.5

90 - 95

97

17

14

.2

46

.7

95 - 99

102

21

17

.5

64

.2

100 -104

107

15

12

.5

76

.7

105 - 109

112

12

10

.0

86

.7

110 - 114

117

5

4

.2

90

.8

115 - 119

122

6

5

.0

95

.8

120 - 124

127

3

2

.5

98

.3

125 - 129

132

1

.8

99

.2

130 - 134

1

.8

.0

137

100

135 - 139

N

120

measures of central tendency1
Measures of Central Tendency

Median (Mdn)

The score that corresponds to the point at or below which 50% of the scores fall. (The 50th percentile.)

slide16

Sample A:26811141620

Mdn = 11.0

Sample B:2681114162051

Mdn = 12.5

2

N

+

1

Median location =

slide17

Grouped Frequency Distribution of IQ scores

Mid-

Cumulative

Value

F

Percent

point

Percent

72

1

.8

.8

70 - 74

4

3

.3

4

75 -79

77

.2

82

8

6

.6

10

.8

80 - 84

8

6

.6

85 - 89

87

17

.5

92

18

15

.0

32

.5

90 - 95

95 - 99

97

17

14

.2

46

.7

102

21

17

.5

64

.2

100 -104

107

15

12

.5

76

.7

105 - 109

12

10

.0

86

.7

110 - 114

112

117

5

4

.2

90

.8

115 - 119

6

5

.0

95

.8

120 - 124

122

127

3

2

.5

98

.3

125 - 129

1

.8

.2

130 - 134

132

99

137

1

.8

100

.0

135 - 139

N

120

slide18

Mean ( 0, :or M)

The average score

å

X

( 3 = capital Sigma = add up all the numbers)

X

=

N

Sample A: 2 6 8 11 14 16 20

77

X

=

=

11

.

0

(Mdn= 11.0 )

A

7

Sample B 2 6 8 11 14 16 20 51

128

( Mdn = 12.5 )

X

=

=

16

B

8

Outlier

slide19

Properties of the mean

0

0

X

X -

X -

2

2 - 11

-9

6

-4

6 - 11

8

8 - 11

-3

11

0

11 - 11

14

3

14 - 11

16

4

16 - 11

9

9

20

20 - 11

0

0

\'

\'

X -

X -

= 0

= 0

slide20

Scores

10

12

15

18

20

Sample A

2

8

15

22

28

Sample B

15

15

15

15

15

Sample C

slide21

M

Scores

Mdn

10

12

15

18

20

15

15

Sample A

2

8

15

22

28

15

15

Sample B

15

15

15

15

15

15

15

Sample C

measures of variability
Measures of Variability

Range

The scale distance between the largest and the smallest scores.

Scores

Mdn

M

12

15

18

20

15

15

Sample A

10

2

8

15

22

28

15

15

Sample B

15

15

15

15

15

15

15

Sample C

RangeA = 20 - 10 = 10

RangeB = 28 - 2 = 26

RangeC = 15 - 15 = 0

slide23

Interquartile Range

Is the distance between the score occuring at the 25th percentile and the score occuring at the 75th percentile.

slide24

Mean (Average) Deviation

å

(

X

-

X

)

N

0

0

X

X -

X -

2

2 - 11

-9

6

-4

6 - 11

8

-3

8 - 11

11

0

11 - 11

14

3

14 - 11

16

4

16 - 11

20

20 - 11

9

9

0

0

\'

\'

X -

X -

= 0

= 0

slide25

Mean Absolute Deviation

å

X

-

X

N

0

0

X

X -

*

X -

*

2

2 - 11

9

6

6 - 11

5

8

8 - 11

3

11

11 - 11

0

14

14 - 11

3

16

16 - 11

4

20

20 - 11

9

9

0

0

\'

\'

X -

X -

= 32

= 32

slide26

Variance (for population)

å

2

(

X

-

X

)

2

s

=

N

0

0

X

Sample

2

)

X -

(X -

A

-5

10

25

12

-3

9

0

0

15

18

3

9

20

5

25

G

0

=

65

68

0

15

=

å

2

(

X

-

X

)

68

2

s

=

=

=

13

.

60

N

5

slide27

Standard Deviation (for population)

å

2

(

X

-

X

)

s

=

N

0

0

X

Sample

2

)

X -

(X -

A

10

-5

25

12

-3

9

0

0

15

18

3

9

5

20

25

G

65

0

68

=

0

15

=

å

2

(

X

-

X

)

68

s

=

=

=

13

.

6

=

3

.

69

N

5

slide28

Variance (for sample)

å

2

(

X

-

X

)

2

s

=

N

-

1

0

0

X

Sample

2

)

X -

(X -

A

10

-5

25

12

-3

9

15

0

0

3

9

18

20

5

25

G

=

65

0

68

0

15

=

å

2

(

X

-

X

)

68

2

s

=

=

=

17

.

00

N

-

1

4

slide29

Standard Deviation (for sample)

å

2

(

X

-

X

)

s

=

N

-

1

0

0

X

Sample

2

)

X -

(X -

A

10

-5

25

12

-3

9

15

0

0

3

9

18

5

20

25

G

=

65

0

68

0

15

=

å

2

(

X

-

X

)

68

s

=

=

=

17

.

0

=

4

.

12

N

-

1

4

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