sampling techniques. simple random sample keep your index card number on you table 1 – random...
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Sampling Techniques
Simple Random SampleKeep Your Index Card Number On You
Table 1 – Random Numbers
92630 78240 19267 95457 53497 23894 37708 79862
79445 78735 71549 44843 26104 67318 00701 34986
59654 71966 27386 50004 05358 94031 29281 18544
31524 49587 76612 39789 13537 48086 59483 60680
06348 76938 90379 51302 55887 71015 09209 79157
The Winners Are!!!!
When you choose members of a sample, you should decide whether it is acceptable to have the some
population member selected more than once. If it is acceptable, then the sampling process is said to be with replacement. If it is not acceptable, then the sampling
process is said to be without replacement.
Replacement
Does Somebody Win More Than Once???
Members of the population are divided into STRATA
Characteristics????
Separate into two subsets – Gender
Hand out Second Set of Index Cards
Stratified Sample
Same number of Ladies and Gentlemen are chosen!!
Members of the population are divided into STRATA
Characteristics????
Separate into three subsets – Low, Medium and High Income
Hand out Third Set of Index Cards
Stratified Sample
Same number people with different incomes are chosen!!
Divide Population into groups called CLUSTERS
Do you all live in Montville Township??
Section of in to different region of Montville Township.
I will choose one of the clusters as my sample.
It is important to make sure that the clusters have similar characteristics!!
Cluster Sample
Back to One Index Card!!
Everyone get in order!!Choose a number between 1 and 6, for our
regular intervals
Systematic Sample
It is the easiest sample but it should be avoided do to regular patterns.
Takes members of a population that are available.
I would like do a surveyTo monitor how students feel when they do too much
math work.
Is any one available to do extra Math Homework???
Convenience Sample
Leads to a Biased Study!!!
1.) Simple Random Sample
2.) Stratified Sample
3.) Cluster Sample
4.) Systematic Sample
5.) Convenience Sample
Review
Chapter 2 – Descriptive Statistics
2.1 – Frequency Distributions and Their Graphs
Sometimes it is possible to collect
all the data for a given population.
Such as the ages of the 50 most powerful women in the world in 2012.
26, 31, 35, 37, 43, 43, 43, 44, 45, 47, 48, 48, 49, 5051, 51, 51, 51, 52, 54, 54, 54, 54, 5, 55, 55, 56, 57, 57,
57, 58, 58, 58, 58, 59, 59, 59, 62, 62, 63, 64, 65, 65, 65, 66, 66, 67, 67, 72, 86
Researchers usually need sample data in order to analyze populations
Frequency Distribution
Organize Data
Histogram
Class Frequency
26 – 34 2
35 – 43 5
44 – 52 12
53 – 61 18
62 – 70 11
71 – 79 1
80 – 88 1
25.5
- 34
.5
34.5
- 43
.5
43.5
- 52
.5
53.5
- 61
.5
61.5
- 70
.5
70.5
- 79
.5
79.5
- 88
.50
4
8
12
16
20
Ages
Add them all and divide by 50
Oldest age – youngest age
Mean and Range
Grouping Data into
Intervals called ClassesAnd forming a
Frequency Distribution
Organize and Describe a Data Set
Class Frequency, f
1 – 5 5
6 – 10 8
11 – 15 6
16 – 20 8
21 – 25 5
26 - 30 4
Frequency Distribution – is table that show classes or intervals of data entries with a count of the number of entries in each class.The frequency f of a class is the number of data entries in the class.
Class Frequency, f
1 – 5 5
6 – 10 8
11 – 15 6
16 – 20 8
21 – 25 5
26 - 30 4
Lower Class Limit – least number that can belong to the class,
Example: 1, 6, 11, 16, 21, 26
Upper Class Limit – greatest number that can belong to the class
Example: 5, 10, 15, 20, 25, 30
The Range is the difference between the maximum and minimum data entries.
Class width are the intervals, the distance from the upper and lower limits of a class.