logging in or signing up sampling Teresa1 Download Post to : URL : Related Presentations : Let's Connect Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Copy embed code: Embed: Flash iPad Dynamic Copy Does not support media & animations Automatically changes to Flash or non-Flash embed WordPress Embed Customize Embed URL: Copy Thumbnail: Copy The presentation is successfully added In Your Favorites. Views: 15761 Category: Education License: All Rights Reserved Like it (6) Dislike it (0) Added: January 30, 2008 This Presentation is Public Favorites: 2 Presentation Description No description available. Comments Posting comment... By: aaartii (14 month(s) ago) This is really nice one Saving..... Post Reply Close Saving..... Edit Comment Close By: mansi123m (31 month(s) ago) gud wrk Saving..... Post Reply Close Saving..... Edit Comment Close By: arunbhuyan (33 month(s) ago) good work.. Saving..... Post Reply Close Saving..... Edit Comment Close By: joyfulljeni (33 month(s) ago) hi can you please do me a favor. . . pls allow us to download this ppt..................... Saving..... Post Reply Close Saving..... Edit Comment Close By: ravikabduwal (33 month(s) ago) Good work..like like Saving..... Post Reply Close Saving..... Edit Comment Close loading.... See all Premium member Presentation Transcript Sampling: SamplingSteps in the Sampling Process: Steps in the Sampling Process Define the population Frame the population Choose a sample design Draw the sample Execute the researchDesigning the Sampling Procedure: Designing the Sampling Procedure Probability (random) samples simple random sampling; systematic sampling stratified sampling cluster sampling Nonprobability samples judgment sampling convenience sampling volunteer sampling quota samplingProbability Samples: Probability Samples When to use stratified sampling over SRS: Primary research objective is to compare groups There are separate confidence interval objectives by strata Variances differ by strata Costs differ by strata Prior information differs by strataProbability Samples: Probability Samples Examples of cluster sampling: Blocks (for consumers); dormitories or classes(for college students) When to use cluster sampling over SRS: When travel costs can be reduced as a result When there are substantial fixed costs associated with each data collection location When there is a list of clusters but not of individual population membersProbability vs. Nonprobability Samples: Probability vs. Nonprobability Samples Probability samples allow hypotheses tests through inferential statistics Biases of nonprobability samples: Subjects not typical of population Easily manipulated Biased toward well-known population members Biased against unusual population members Probability vs. Nonprobability Samples: Probability vs. Nonprobability Samples Nonprobability samples are adequate when: the sample is very small the population is homogenous on the variable being studied informal, exploratory research is being done it is desired to screen out “loser” productsDiscussion: Discussion Provide the marketing researcher’s definitions for each of the following populations: Columbia House, a mail order house specializing in tapes and CDs, wants to determine interest in a 10-for-1 offer on hard rock CDs. The manager of your student union is interested in determining if students desire a “universal checking account ID card” that will be accepted anywhere on campus and in many stores off campus. Joy Mfg. Co. decides to conduct a survey to determine the sales potential of a new type of air compressor used by construction companies.Discussion: Discussion Taco Bell approaches an official at your university and proposes to locate one of its restaurants on campus. Because it would be the first commercial interest of this sort on this campus, the administration requires Taco Bell to conduct a survey of students to assess the desirability of this operation. Analyze the practical difficulties with doing a census in this situation, and provide specific examples of each one. For example, how long might such a census take? How much might it cost? What types of students are more accessible than others?...Sampling and Nonsampling Errors: Sampling and Nonsampling Errors Nonsampling error: Unrelated to the sampling of respondents Sampling error Samples do not always reflect a populations’ true characteristics. Controlled by sample size. Sample bias Members of sample differ from larger population in some systematic fashion. Controlled by defining population and selective representative sample.Sampling Error: Sampling Error Sampling error is the standard deviation of the distribution of sample means. The larger the sample, the smaller the sampling errorThe Confidence Interval Approach: The Confidence Interval Approach Confidence intervals Example: 95% of values in normal distribution fall within ± 1.96 standard deviations from the mean of the distribution. Therefore, for the population mean, 95% of values in normal distribution will fall within the interval The Confidence Interval Approach: The Confidence Interval Approach To determine sample size using a mean: Use the formula For 95% CI, z = 1.96 Must estimate s Must assign a value to eThe Confidence Interval Approach: The Confidence Interval Approach To determine sample size using a percentage: Use the formula For 95% CI, z = 1.96 Must estimate p. Then, q = 1 - p Must assign a value to eThe Confidence Interval Approach: How to estimate variability in a population: Prior research (secondary sources,…) Experience Intuition Range divided by 6 (for means) Worst possible scenario = .5 (for percentages) How to determine amount of precision desired: Cost and feasibility of having a large sample Client’s tolerance for uncertainty The Confidence Interval ApproachDiscussion: Discussion Last year, Lipton Tea Company conducted a mall-intercept study at six regional malls in the U.S. and found that 20% of the public preferred tea over coffee as a mid-afternoon hot drink. This year, Lipton wants to have a nationwide telephone survey performed with random digit dialing. What sample size should be used in this year’s study in order to achieve an accuracy level of ± 2.5% at the 99% level of confidence? What about at the 95% level of confidence?Value of Information Approach: Value of Information Approach CI method ignores: Relative importance of project New versus old products Cost per observation Value of information is more decision-oriented: best for “problem solving” researchValue of Information Approach: Value of Information Approach Factors relating to the value of information: Uncertainty about the proper course of action Gains or losses available from the decision Nearness to breakeven Calculating sample size. Two main considerations: marginal value of additional units decreases marginal cost of additional units increases Nonstatistical Approaches: Nonstatistical Approaches Using previous sample sizes Using typical sample sizes Using a “magic number” Anticipation of subgroup analyses Use of resource limitations Use of expert guidanceDiscussion: Discussion What sample size would you use? Why? Design for a new microwave oven Major new product introduction for company Research objective: what would the market share for this new product be? Previous introductions: Similarly-designed conventional oven: 36% of those questioned prefer new design over any other Similarly-designed deep fryer: 17% of those questioned prefer new design over any other 1% market share = $5,000,000 You do not have the permission to view this presentation. In order to view it, please contact the author of the presentation.