State Population Questions
State Populational45nh13nj86nd06oh114ok35or36pa124ri11sc41sd
State Populational45nh13nj86nd06oh114ok35or36pa124ri11sc41sd
State Population AL4.5 NH1.3 NJ8.6 ND0.6 OH11.4 OK3.5 OR3.6 PA12.4 RI1.1S C4.1S D0.8 TN5.8 TX22.1 UT2.4 VT0.6 VA7.4 WA6.1 WV1.8 WI5.4 WY0.5 CO45 AK 0.6 CT3.5 AZ5.5 DE0.8 AR2.7 FL17.0 CA35.5 GA8.6 HI1.3 ID1.4 IL12.7 IN6.2 IA2.9 KS2.7 KY4.1 LA4.5 ME1.3 MD5.5 MA6.4 MI10.0 MN5.1 MS2.9 MO5.7 MT0.9 NE1.7 NV2.2 NH1.3 NJ8.6 ND0.6 OH11.4 OK3.5 OR3.6 PA12.4 RI1.1S C4.1S D0.8 TN5.8 TX22.1 UT2.4 VT0.6 VA7.4 WA6.1 WV1.8 WI5.4 WY0.5 Practice Sampling Problems This exercise gives you an opportunity to practice some of the sampling techniques described in the chapter. The following is a list of the states in the United States (abbreviated) and their populations in 2005 to the nearest tenth of a million. 1 1. Number the states from 01 to 50, entering the numbers next to the abbreviated name on the list. 2. Use the random number table in Appendix E and select enough two-digit numbers to provide a sample of 12 states. Write all the numbers and cross out the ones you don’t use. 3. List the 12 states that make it into your random sample. 4. Now, if you have easy access to the Internet, locate the Research Randomizer (draw one set of 12 numbers from 01 to 50 from it. Then list the 12 states that would make it into your random sample this time. 5. This time, take a stratified random sample of 10 states, one of which has a population of 10 million or more and nine of which have populations of less than 10 million. List the states you chose. 6. How might you draw a quota sample of 10 states, one of which has a population of 10 million or more and nine of which have populations of less than 10 million? A. Describe one way of doing this B. Describe, in your own words, the most important differences between the sampling procedures used in Questions 5 and 6a. A copy of the sampling chart with at least 13 numbers is provided; you may use these or others as preferred. The numbers are grouped in four, with only the last two used as highlighted.
Paper For Above instruction
The given exercise involves practicing different sampling techniques using a list of U.S. states and their populations in 2005. These techniques include simple random sampling, stratified sampling, and quota sampling. The purpose is to understand how to select representative samples for research purposes, emphasizing the practical application of these methods and their implications for validity and reliability.
Firstly, the task requires assigning numbers to each state from 01 to 50, then selecting a sample of 12 states using a random number table. The process involves noting the numbers, eliminating repetitions or unwanted selections, and listing the corresponding states. A second approach involves using an online randomizer tool to generate a different set of 12 states, illustrating the use of computer-based random selection.
Next, the exercise introduces stratified sampling, which involves dividing the population into subgroups based on a characteristic—in this case, population size—and then randomly selecting members from each subgroup. Specifically, one state with a population of 10 million or more and nine with less than 10 million are chosen, reflecting the importance of ensuring representation across different strata.
Finally, the exercise explores quota sampling, a non-random but structured technique where the researcher ensures the presence of specific subgroups—here, one large-population state and nine smaller ones—by predetermined quotas. Comparing this with stratified sampling highlights key differences: stratified sampling involves random selection within strata, maintaining probability-based representativeness, whereas quota sampling relies on convenience or judgment to fill quotas, which can introduce bias.
In addition to these sampling exercises, there is a component related to developing measurement strategies within social sciences. It involves selecting an area (e.g., aging, crime), defining a concept (e.g., attitudes towards elderly), and operationalizing it through specific indicators and categories. The process includes determining the level of measurement—nominal, ordinal, interval, or ratio—and discussing the reliability and validity of the chosen measurement methods, along with strategies for assessing these qualities.
Understanding and applying these sampling techniques and measurement strategies are crucial for conducting valid social science research. These methods ensure that data collected are representative, reliable, and capable of accurately capturing the phenomena under study, thereby informing effective policies and interventions.
References
- Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley.
- Survey Research Methods (5th ed.). Sage Publications.