Descriptive and Inferential Statistics - Types of Sampling Errors - Statistics Assignment Help

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Task: In your own words, define and give an example of each of the following statistical terms:
  1. a) Population
  2. b) Sample
  3. c) Parameter
  4. d) Statistic
  5. e) Statistical inference
1.2 Briefly describe the difference between descriptive statistics and inferential statistics. 1.3 The manager of a bank with 12000 customers commissions a survey to gauge customer views on internet banking, which would incur lower bank fees. In the survey, 21% of the 300 customers interviewed said they are interested in internet banking.
  1. a) What is the population of interest?
  2. b) What is the sample?
  3. c) Is the value 21% a parameter or a statistic?
1.4 A light bulb manufacturer claims that less than 5% of his bulbs are defective. When 1000 bulbs were drawn from a large production run, 1% were found to be defective.
  1. a) What is the population of interest?
  2. b) What is the sample?
  3. c) What is the parameter?
  4. d) What is the statistic?
  5. e) Does the value 5% refer to the parameter or to the statistic?
  6. f) Is the value 1% a parameter or a statistic?
  7. g) Explain briefly how the statistic can be used to make inferences about the parameter to test the claim.
2.1 Provide two examples each of numerical, ordinal and nominal data. 2.5 A random sample of 100 university academics was taken. Each academic was asked the following questions. Identify the type of data.
  1. a) What is your rank (lecturer, senior lecturer, associate professor, professor)?
  2. b) What is your annual salary?
  3. c) In which faculty (Arts, Science, Business, Engineering, etc.) of the university are youemployed?
  4. d) For how many years have you been an academic?
  5. e) How many different courses have you taught?
2.16 a) List three methods of conducting a survey of people.
  1. b) Give an important advantage and disadvantage of each of the methods listed in part (a).
2.25 Briefly describe three types of sampling errors.
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