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STATISTIK DESKRIPTIF

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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STATISTIK DESKRIPTIF

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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

    10. Reproductive Conflict Resolution: What to Do if Only One Partner Wants Another Child

    11. Reproductive Conflict Resolution: What to Do if Only One Partner Wants Another Child

    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.

    22. Outcomes from Reproductive Conflict: Raw Frequencies

    23. Outcomes from Reproductive Conflict: Percentage Distribution

    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

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