| 1.
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Identify the difference between descriptive and inferential
statistics. (I)
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| 2.
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Distinguish between a population and a sample. (II)
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| 3.
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Group a set of data and present the grouping in graphical form. (II)
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| 4.
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Determine the mean, median, mode and standard deviation of data set
and find the z-score for a data piece. (III)
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| 5.
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Define random variable and the probability distribution of a random
variable. (IV)
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| 6.
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Find probabilities for normal random variables by using the standard
normal distribution. (V)
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| 7.
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Construct random samples. (VI)
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| 8.
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Graph the sampling distribution of the mean for all sample sizes and
all populations. (VI)
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| 9.
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Find point and interval estimates of population means and proportions.
(VII)
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| 10.
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Describe the logic of hypothesis testing emphasizing the role of
probability distributions and types of error. (VIII)
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| 11.
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Perform inferences about one mean or proportion in the case of normal
populations or large sample size. (VIII)
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| 12.
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Perform inferences about two means or proportions in the case of
normal populations or large sample size. (IX)
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| 13.
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Use the Chi-square goodness-of-fit test to determine if two
populations have the same shape. (X)
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| 14.
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Use the Chi-square independence test to determine whether two
characteristics of a population are associated (dependent). (X)
|
| 15.
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Identify the best-fitting regression line for a set of data points.
(XI)
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| 16.
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Partition the total sum of squares for a set of data points to find
measures of regression line fit and linear relationship. (XI)
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