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RANDOM SAMPLING

RANDOM SAMPLING. POPULATION- the entire group of individuals that we want information about SAMPLE- the part of the population that we actually examine in order to gather information about the population. Population vs. Sample. Gallup finds unemployment at 10.1% in September

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RANDOM SAMPLING

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  1. RANDOMSAMPLING

  2. POPULATION- the entire group of individuals that we want information about • SAMPLE- the part of the population that we actually examine in order to gather information about the population

  3. Population vs. Sample • Gallup finds unemployment at 10.1% in September • The findings were based on more than 18,146 phone interviews (random digit dialing) with U.S. adults aged 18 and older • POPULATION: all U.S. adults ages 18 and older who have telephones • SAMPLE: 18,146 U.S. adults with telephones

  4. SIMPLERANDOM SAMPLE (SRS) • A SRS (of size n) is selected from a population in a way that every different possible sample of size n has the same probability of being selected • Select an SRS of size 3 from our AP Stat course • All possible groups of 3 students have the same probability of being selected as any other group of 3 students • Not an SRS: Split students into males and females. Randomly select one female and two males.

  5. Constructing an SRS • Create a list of the sampling frame • Give each object a number • Use a random number table to select sample • An Example: Randomly select 4 students from our AP Stat class • List all students available for selection • Give each student a number • Since the largest number of students that we can select only has two digits, we will take numbers in groups of 2 (start on line 130 of Table B)

  6. Line 130 of the Random Number Table

  7. Generating Random Numbers on the TI Graphing Calculator • 7  Math, rand, enter (change random seed #) • Math >>> 5 (PRB) • randInt (min,max) • Note: If a number is selected more than once, ignore it

  8. Stratified Random Sample • The population is divided in to at least two distinct groups (strata). • A simple random sample of a certain size is drawn from each strata. • Often, the size is chosen by using the actual percentage of occurrence in the overall population • Example: Divide class into girls and boys and randomly select from each gender in the proportion that they occur in the population (class).

  9. Cluster Sample • Divide the population into subgroups (clusters) • Select clusters at random • Include all individuals in the selected clusters in your study • Example: Randomly select homerooms and then include all students in the homerooms in the sample • In class, randomly select a row, include all students in the row to be in the sample • Multi-Stage Cluster Sample

  10. Systematic Sampling • The elements in the population should already be arranged in some natural sequential order • Choose every kth element in the population to be part of your sample • List the students in AP Statistics alphabetically • Number the students • Randomly select a student • Choose every kth student depending on the size of your sample • K = N/n = ________ Round down. Choose every _______ student

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