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A company developed a smartphone whose average lifetime is unknown. In order to estimate the
average, 200 smartphones are randomly selected from a large production line and tested; their
average is found to be 5 years. The 200 smartphones represent: - - a sample
Significance level - - Measures the reliability of a statistical inference
inferential statistics - - Process of using sample statistics (mathematics) to draw conclusions
about population parameters
mutually exclusive - - Events that cannot occur at the same time.
sampling error - - the difference between the results of random samples taken at the same
time
non-sampling error - - occurs when the sample data are incorrectly collected, recorded, or
analyzed. Three types of errors: data acquisition errors, non-response errors (or bias), selection
bias
Design of a good survey components - - short survey, short/simple questions, start with
demographic questions, ues dichtomous (yes-no) and multiple choice
Direct observation - - example: counts backpacks on campus for a day
stratified random sample - - a sample from selected subgroups of the target population in
which everyone in those subgroups has an equal chance of being included in the research
, example: The manager of a customer service division wants to know if the customers in the past 12
months are satisfied with their purchase of CD's. There are four types of CD's.
Joint Probability - - the probability of the intersection of two events
Union of two events - - The union of events A and B is the event containing all sample points
that are in A or B or both
Marginal Probability - - the probability of a single event without consideration of any other
event
Conditional Probability - - the likelihood that a target behavior will occur in a given
circumstance
Bayes Law - - calculates posterior probability
exhaustive - - including everything possible; very thorough or complete
Central Limit Theorem (CLT) - - The name of the theorem stating that the sampling
distribution of a statistic (e.g. x ) is approximately normal whenever the sample is large and random.
Allows us to draw conclusions about the population based on strictly sample data.
sampling distribution of the mean - - 1. the sampling distribution of the mean has a different
mean from the original population
2. the standard deviation of the sampling distribution of the mean is referred to as the standard
deviation
3. if the original population is not normally distributed, the sampling of the mean will be normal
Suppose you are given 3 numbers that relate to the number of people in a sample. The three
numbers are 10, 20 and 30. If the standard deviation is 10, the standard error equals - - 5.77