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Quantitative Research Techniques + Statistics – Peregrine Exam
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Quantitative Research Techniques +Statistics – Peregrine Exam
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
To find the standard deviation, find the mean of the data set ( 10, 20, 30)
then calculate in excel. Watch video Bozeman Science Standard Error
-Find the sample standard deviation of 5, 10, 15 and 20. - -6.45
-standard deviation - -a computed measure of how much scores vary
around the mean score
-Type 1 error - -Rejecting null hypothesis when it is true
-type 11 error - -false negative
-Type 1 error criminal - -Innocent person is wrongly convicted
-The hypothesis of most interest to the researcher is: - -the alternative
hypothesis
-p-value - -The probability level which forms basis for deciding if results are
statistically significant (not due to chance).
-Variance - -the square of the standard deviation
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