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Data Collection Methods. In a population there is a parameter of interest whose value is unknown. We use a sample estimator to estimate the value of this.

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Presentation on theme: "Data Collection Methods. In a population there is a parameter of interest whose value is unknown. We use a sample estimator to estimate the value of this."— Presentation transcript:

1 Data Collection Methods

2 In a population there is a parameter of interest whose value is unknown. We use a sample estimator to estimate the value of this parameter. The sample estimator is called a sample statistic.

3 Some common parameters and sample statistic NameStatisticParameter MeanSample meanPopulation mean Standard deviationSample std deviationPopulation std deviation correlationsample correlation coefficient Population correlation coefficient proportionSample proportionPopulation proportion

4 Data Collection Methods It is critical to get “Good Sample”. Good Sample is one that fairly represents every member of the population How do we get a good sample?

5 Data Collection Methods Examples 1.Internet polling 2.Telephone surveys 3.Taking surveys at the mall 4.Surveys through mail or e-mail

6 Data Collection Methods Basic Principles of Getting Good Sample Randomize: Select your sample randomly. Assign numbers to members of the population Use a random number generator to select your sample

7 Data Collection Methods Sample size is important! You need a large enough sample so that you can get fair representation.

8 Data Collection Methods Types of Samples Simple Random Sample (SRS): A sample in which every group of n individuals has the same chance of being selected. Example: Select 5 students from a class of 50 students Use Excel’s random number generator.

9 Data Collection Methods Stratified Samples: Used for large population sizes. First divide the entire population into groups (with common characteristics). Such groups are called strata. Within each stratum use simple random sampling method

10 Data Collection Methods Cluster sampling: Divide the population into some clusters or groups. Then select randomly few clusters and perform simple random sampling in the clusters selected.

11 Data Collection Methods Multistage Sampling: Divide the population into some clusters or groups. Select few groups randomly Divide the selected groups further into smaller parts Then select a simple random sample from each part


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