Conduct a survey then display and analyze the data using methods from Chapters 2 and 3 of your textbook. Use techniques of inferential statistics (Chapters 7-9) to construct a confidence interval and complete a test of hypothesis.
Part I: Pick a theme and gather the data
– Pick a theme (topic) that will explore a comparison between two populations.
– Define two distinct populations and two independent samples, for example: Population 1: Male Students at DVC, Population 2: Female Students at DVC. Two populations or samples are independent if the values selected from one population are not related to or somehow naturally paired or matched with the values selected from the other population.
– Devise a sampling technique. A SRS is not expected but it should be more than a mere convenience sample. Sampling techniques are discussed in Chapter 1.
– Write a sample survey that includes at least 1 qualitative question (could be used to define your two independent samples) and 1 quantitative question. The quantitative data should be continuous and not discrete. Gather raw data, not grouped (you will group it later into classes). Pay close attention to the wording of your questions and also any units of measure you are planning to use. Don’t make your questions unnecessarily complicated!
– Conduct your survey. Each of the two independent samples must have a sample size greater than 30. You can use a paper sample, phone sampling or conduct your survey electronically using something like Survey Monkey or StatCrunch.
– Compile your results in a spreadsheet. StatCrunch has a spreadsheet or you can use something like EXCEL or Numbers.
Part II: The Report Use your data to write your report with the following minimum requirements:
– Title page including your names and theme.
– Description of your populations and samples
– Description of your sampling technique
– A blank copy of your survey/questions
– At least 1 pie chart or bar/pareto chart using qualitative data
– At least one distribution chart that includes columns for frequency, percentage frequency and cumulative frequency. This chart should include 5-8 classes.
– At least one histogram and one frequency polygon (2 graphs)
– Summary statistics for both independent samples using your quantitative data. Include the following: sample size, sample mean, sample standard deviation, sample variance, 5-number summary, range of usual values (those within 2 standard deviations of the mean).
– Two modified box plots, one for each 5-number summary (see p.121).
– Construct a 95% confidence interval to compare your two populations using your quantitative data. Include a complete interpretive sentence (see p.301).
– Complete a test of hypothesis to compare your two populations using your quantitative data using the p-value method and techniques from Chapter 8 and Chapter 9. Include the hypotheses, p-value and a proper conclusion (see p.364 flowchart).
– Finish with a very well-written paragraph or two that compares/contrasts the data sets to make some valid conclusions about the populations based upon your data. To be clear, valid conclusions about the populations are not a simple summary of what you observe in the sample data. What you observe in the sample data cannot be extended to the entire population unless the correct statisitacal analysis has been done to support doing so. Your conclusions should be based on the results of the analysis and include your confidence level.