1.3 Populations, Samples, and Sampling Techniques Chapter 1 (Page 38)

Population – the set of all objects or individuals of interest or the measurements obtained from all objects or individuals of interest. Sample – a subset of the population (Page 39) Parameters – descriptive numerical measures computed from an entire population Statistics – descriptive numerical measures computed from a sample

When a teacher wants to know the common height of freshmen students in YUC, she gets only a sample of 200 first year students. When a housewife buys a sack of rice, she examines only a handful of rice from the sack to find out whether it is of good quality or not. When a researcher wants to know the IQ of students in the international high schools, she gets a sample of 50 first to fourth year students from each of the international high schools in Yanbu.

(Page 39) Statistical Sampling Techniques – methods that use selection techniques based on chance selection Non-statistical Sampling Techniques – methods of selecting samples using convenience, judgment or other nonchance processes. Convenience Sampling – techniques that selects the items from the population based on accessibility and ease of selection

(Page 40) Statistical Sampling Methods – (probability sampling) allow every item in the population to have a chance of being included in the sample. (Page ) 1.Simple Random Sampling – items from a population has an equal chance of being selected. 2.Stratified Random Sampling – items are selected from each stratum (group) using the simple random sampling.

(Page 42 – 43) 3. Systematic Random Sampling – selecting every kth item in the population after a randomly selected starting point between 1 and k. 4. Cluster Sampling – method in which the population is divided into clusters that are intended to be mini-population.

1.4 Data Types and Data Measurement Levels Chapter 1 (Page 44)

(Page 45) Quantitative Data – measurements whose values are numerical. Qualitative Data – measurements is categorical. Sample Exercises: 1.Amount of time it takes to assemble a simple puzzle. 2.Number of students in a first-grade classroom. 3.Rating of newly elected politician: excellent, good, fair, poor. 4.State in which a person lives.. 5.Population in a particular area of the US. 6.Age of a cancer patient. 7.Color of a car entering in a parking lot.

Additional Exercise: 1. 1.Most frequent use of microwave oven. (reheating, defrosting, warming) 2. 2.Number of consumers who refuse to answer a telephone survey The door chosen by a mouse in a maze experiment. (A, B, or C) 4. 4.The winning time for a horse in a derby The number of children who are reading above grade level.

(Page 45) Time-Series Data – a set of consecutive data values observed at successive points in time. Example: yearly enrollment, daily sales, quarterly production Cross-Sectional Data – set of data values observed at a fixed point in time. Example: annual income of household for year 2000, average salary of teachers at YUC for year 2009

(Page ) Data Measurement levels Data Measurement levels 1.Nominal Data – lowest form of data assigning codes to categories. 2.Ordinal Data – data elements are rank-ordered on the basis of some relationship with the assigned values indicating this order. 3.Interval Data – data items can be measured on scale and the data have ordinal properties. 4.Ratio Data – have a true zero point.

(Page 47) Example 1 – 1 Categorizing Data News and World Report Step 1. Identify each factor in the data set. Step 2. Determine whether the data are time- series or cross-sectional. series or cross-sectional. Step 3. Determine which factors are quantitative or qualitative data. quantitative or qualitative data. Step 4. Determine the level of data measurement for each factor. measurement for each factor.

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Exercises 1-32, 1-34, 1-35 Exercises 1-32, 1-34, Population – all objects or individuals Sample – subset of population 1-34 a. Cluster Random Sampling b. Stratified Random Sampling c. Convenience Sampling 1-35not on chance selection/convenience sampling selection/convenience sampling

(Page 43) Additional Exercises: 1 – 38, 1 – 42, 1 – 43 Answers: 1-38Statistics 1-42Statistics 1-43a. Cluster/Stratified Random Sampling b. Simple Random Sampling c. Systematic Random Sampling d. Stratified Random Sampling

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Exercises :1-49,1-51, a. time-series1-55a. nominal b. cross sectionalb. ratio c. time-seriesc. nominal d. cross sectionald. ratio e. ratio 1-51a. ordinalf. nominal b. nominalg. ratio c. ratio d. nominal