statistik deskriptif cara penyajian data

STATISTIK DESKRIPTIF

Isi:

Pengenalan tipe data dan cara penyajian data

Basic Business Statistics: Concepts & Applications

Presenting Data in Tables & Charts

Numerical Data Presentation

OrderedArray

OgivePolygonHisto-gram

FrequencyDistributions

NumericalData

Stem-&-LeafDisplay

Ordered Array

• 1. Organizes Data to Focus on Major Features

• 2. Data Placed in Rank Order – Smallest to Largest

• 3. Data in Raw Form (as Collected)– 24, 26, 24, 21, 27, 27, 30, 41, 32, 38

• 4. Data in Ordered Array– 21, 24, 24, 26, 27, 27, 30, 32, 38, 41

Numerical Data Presentation

OrderedArray

OgivePolygonHisto-gram

FrequencyDistributions

NumericalData

Stem-&-LeafDisplay

Stem-and-Leaf Display

• 1. Divide Each Observation into Stem Value and Leaf Value– Stem Value Defines

Class

– Leaf Value Defines Frequency (Count)

2 144677

3 028

4 1

2. Data: 21, 24, 24, 26, 27, 27, 30, 32, 38, 41

26

Numerical Data Presentation

OrderedArray

OgivePolygonHisto-gram

FrequencyDistributions

NumericalData

Stem-&-LeafDisplay

Frequency Distribution Table

Raw Data: 24, 26, 24, 21, 27, 27, 30, 41, 32, 38

Class Frequency

15 but < 25 3

25 but < 35 5

35 but < 45 2

Frequency Distribution Table Steps

• 1. Determine Range

• 2. Select Number of Classes– Usually Between 5 & 15 Inclusive

• 3. Compute Class Intervals (Width)

• 4. Determine Class Boundaries (Limits)

• 5. Compute Class Midpoints

• 6. Count Observations & Assign to Classes

Frequency Distribution Table Example

Raw Data: 24, 26, 24, 21, 27, 27, 30, 41, 32, 38

Boundaries (Upper + Lower Boundaries) / 2

Width

Class Midpoint Frequency

15 but < 25 20 3

25 but < 35 30 5

35 but < 45 40 2

Relative Frequency & % Distribution Tables

Percentage Distribution

Relative Frequency Distribution

Class Prop.

15 but < 25 .3

25 but < 35 .5

35 but < 45 .2

Class %

15 but < 25 30.0

25 but < 35 50.0

35 but < 45 20.0

Cumulative Percentage Distribution Table

Percentage Less than Lower Class Boundary

Raw Data: 24, 26, 24, 21, 27, 27, 30, 41, 32, 38

Lower Class Boundary

30% + 50%

80% + 20%

Class CumulativePercentage

15 but < 25 0.0

25 but < 35 30.0

35 but < 45 80.0

45 but < 55 100.0

Numerical Data Presentation

OrderedArray

OgivePolygonHisto-gram

FrequencyDistributions

NumericalData

Stem-&-LeafDisplay

0

1

2

3

4

5

Histogram

Frequency

Relative Frequency

Percent

0 15 25 35 45 55

Lower Boundary

Bars Touch

Class Freq.15 but < 25 325 but < 35 535 but < 45 2

Count

Numerical Data Presentation

OrderedArray

OgivePolygonHisto-gram

FrequencyDistributions

NumericalData

Stem-&-LeafDisplay

0

1

2

3

4

5

Polygon

Midpoint

Fictitious Class

0 10 20 30 40 50 60

Class Freq.15 but < 25 325 but < 35 535 but < 45 2

Frequency

Relative Frequency

Percent

Count

Numerical Data Presentation

OrderedArray

OgivePolygonHisto-gram

FrequencyDistributions

NumericalData

Stem-&-LeafDisplay

0%

25%

50%

75%

100%

Cumulative % Polygon (Ogive)

Lower Boundary

Fictitious Class

0 15 25 35 45 55

Class Cum. %15 but < 25 0%25 but < 35 30%35 but < 45 80%45 but < 55 100%

Cumulative %

Errors in Presenting Data

• 1. Using ‘Chart Junk’

• 2. No Relative Basis in Comparing Data Batches

• 3. Compressing the Vertical Axis

• 4. No Zero Point on the Vertical Axis

‘Chart Junk’

Bad Presentation Good Presentation

1960: $1.00

1970: $1.60

1980: $3.10

1990: $3.80

Minimum Wage Minimum Wage

0

2

4

1960 1970 1980 1990

$

No Relative Basis

Good Presentation

A’s by Class A’s by Class

Bad Presentation

0

100

200

300

FR SO JR SR

Freq.

0%

10%

20%

30%

FR SO JR SR

%

Compressing Vertical Axis

Good Presentation

Quarterly Sales Quarterly Sales

Bad Presentation

0

25

50

Q1 Q2 Q3 Q4

$

0

100

200

Q1 Q2 Q3 Q4

$

No Zero Point on Vertical Axis

Good Presentation

Monthly Sales Monthly Sales

Bad Presentation

0

20

40

60

J M M J S N

$

36

39

42

45

J M M J S N

$

Categorical Data Presentation

ParetoDiagram

PieChart

CategoricalData

1 Variable

BarChart

SummaryTable

Summary Table

• 1. Lists Categories & No. Elements in Category

• 2. Obtained by Tallying Responses in Category

• 3. May Show Frequencies (Counts), % or Both

Row Is Category

Tally:|||| |||||||| ||||

Major CountAccounting 130Economics 20Management 50Total 200

Categorical Data Presentation

ParetoDiagram

PieChart

CategoricalData

1 Variable

BarChart

SummaryTable

0 50 100 150

Acct.

Econ.

Mgmt.

Bar Chart

Horizontal Bars for Categorical Variables

Bar Length Shows Frequency or %

1/2 to 1 Bar Width

Equal Bar Widths

Zero Point

Frequency

Major

Percent Used Also

Categorical Data Presentation

ParetoDiagram

PieChart

CategoricalData

1 Variable

BarChart

SummaryTable

Econ.10%

Mgmt.25%

Acct.65%

Pie Chart

• 1. Shows Breakdown of Total Quantity into Categories

• 2. Useful for Showing Relative Differences

• 3. Angle Size– (360°)(Percent)

Majors

(360°) (10%) = 36°

36°

Categorical Data Presentation

ParetoDiagram

PieChart

CategoricalData

1 Variable

BarChart

SummaryTable

0%

33%

67%

100%

Acct. Mgmt. Econ.

Pareto Diagram

Percent

Major

Descending Order

Cumulative Polygon (Ogive)

Equal Bar Widths

Vertical Bar Chart

Bar Midpoint

Always %

Thinking Challenge

•You’re an analyst for IRI. You want to show the market shares held by Windows program manufacturers in 1992. Construct a bar chart, pie chart, & dot chart to describe the data.

• Mfg. Mkt. Share (%)•Lotus 15•Microsoft 60•WordPerfect 10•Others 15