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Basic Descriptive Statistics. . Basic Descriptive Statistics. Percentages and proportionsRatios and ratesFrequency distributions. Why?. To interpret others' dataTo present own data clearly. How?. Through data reduction. Data Reduction. Makes a mess of numbers understandableInvolves loss of preci
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1. STATISTIK DESKRIPTIF Isi:
Konsep Statistik Deskriptif
Grafik untuk Statistik Deskriptif
2. Basic Descriptive Statistics
3. Basic Descriptive Statistics Percentages and proportions
Ratios and rates
Frequency distributions
4. Why? To interpret others’ data
To present own data clearly
5. How? Through data reduction
6. Data Reduction Makes a mess of numbers understandable
Involves loss of precision and detail
8. What is gained and lost? Simpler message
Ability to easily compare groups of different sizes Lose information on sample size
Make it seem as if groups may be more comparable than they are
9. Rules for handling percentages and proportions well Don’t calculate when n<20
Always report n along with percentages and proportions
Be suspicious when presented with percentages and proportions without n
Appropriate for any level of measurement
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12. Rates and Ratios
13. Ratios Expresses the relative frequency of two categories
Often expressed without decimals
Often expressed with a colon, e.g, 2:1
14. Rates The number of actual occurrences over possible occurrences per unit of time
CDR, IMR, CPR
Some rates don’t fit the technical definition, e.g, CBR
15. Frequency distributions Definition: a table that displays the number of cases in each category of a variable
Any frequency distribution must have mutually exclusive and exhaustive categories
Appropriate for all levels of measurement
Label well: title, columns, rows, n
More than one frequency distribution can be in a single table
16. Graphical Presentation
17. Charts and Graphs Goal: Convey an impression of the overall shape of a distribution and for highlighting any clustering of cases in a particular range of scores
Which chart or graph type is dependent upon the type of variable and level of measurement
18. Pie Chart Appropriate for nominal variables (also sometimes used for ordinal or interval-ratio variables)
Convert the percentage distribution from the frequency distribution into appropriately sized ‘pie slice’
Label each pie slice Go through an example of how to construct pie chart on blackboard.
Use u men data from earlier slide.
Ask what kind of data
Are the categories mutually exclusive and exhaustive?
360x.05=18; 360x.30=108; 360x.08=29; 360x.49=176; 360x.05=18Go through an example of how to construct pie chart on blackboard.
Use u men data from earlier slide.
Ask what kind of data
Are the categories mutually exclusive and exhaustive?
360x.05=18; 360x.30=108; 360x.08=29; 360x.49=176; 360x.05=18
21. Bar Chart Appropriate for nominal variables with more than five categories or ordinal variables
Convert the percentage distribution from the frequency distribution into appropriately sized bars.
Label both the x and y axis and use appropriate tick marks.
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24. Moral Frequency distributions and percentage frequency distributions have the same shape for a given sample
When n differs between samples, frequency distributions can be misleading
Percentage frequency distributions are then preferable when there is more than one sample, but be sure to disclose n
25. Histograms Appropriate for interval-ratio variables
Look like bar charts, but the bars ‘touch’
Like a frequency distribution, the data must first be converted from the interval-ratio level to the ordinal level
Construct similarly as a bar chart; label x & y axes and use appropriate tick marks
26. Choosing the number of class intervals for interval-ratio data A trade-off between detail and summary
Your book says 10-15, sometimes fewer; I think often fewer
All intervals must be equal in size (with some exceptions for lowest and highest)
N/k should be at least 5
27. Combining Class Intervals without Loss of Information
29. Real and Nominal Limits Nominal limits are the ones presented
Real limits are at a higher degree of precision
30. Line Chart or Frequency Polygon Appropriate for interval-ratio variables
Construct similarly to a histogram
Instead of using bars to represent the percentages, use a dot at the midpoint of each interval
‘Connect the dots’ with straight lines
Often used to show trend across time
32. Cumulative Frequency and Cumulative Percentage (not in your book) Not appropriate for nominal data
Uses the frequency in the class interval and all preceding class intervals
Line charts use endpoints of class intervals
cumulative frequency polygons do not return to zero (frequency polygons can if the last measurement class is not open-ended)
33. Frequency Distribution from Previous Line Chart
34. Cumulative Frequency Distribution GRAPH!GRAPH!
35. How to Describe Frequency Distributions Central tendency
Dispersion
Categories with lower than average & higher than average frequencies
Do categories with similar frequency have anything else in common?
For interval-ratio, symmetry or skewedness