Download Terms: Statistics, Descriptive Statistics, Inferential Statistics

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Statistics, Descriptive Statistics, Inferential Statistics, Probability, Deductive Thought Process,
Inductive Thought Process, Population, Sample, Parameter, Statistic, Census, Random Sample,
Simple Random Sample, Sampling Frame, Sampling Bias, Stem-and-Leaf Plot, Leaf Unit,
Increment, Split stems, Modes, Shapes of Distributions, Frequency Distribution, Relative
Frequency Distribution, Class Cutpoints, Class Midpoint, Class Width, Histogram, Mean,
Median, Robust, Range, First and Third Quartiles, Interquartile Range, Five-Number Summary,
Boxplot, Fences, Whiskers, Variance, Standard Deviation, Probability experiment, Outcome,
Sample space, Event, Probability of an event, Null event, Simple Event, Union event,
Intersection event, Complement of an event, Mutually exclusive events, Independent events,
Addition rule for mutually exclusive events, Complement rule, Multiplication rule for
independent events, Conditional probability of B given A, Multiplication rule, Addition rule
Sample mean, Sample median, Range, First and third quartiles, Interquartile range, Sample
variance, Sample standard deviation, Population mean, Population variance, Sample space,
Event, List method for denoting events, Probability of an event, Null event, Union event,
Intersection event, Complement of an event, Conditional probability of B given A
3 reasons to take a sample, 4 main features of the distribution, 3 graphical summaries of
quantitative data, 2 things to look for when determining the shape of a distribution (number of
modes, symmetry or skewness), 2 measures of center, 5 measures of variation (or spread), 3
axioms of probability, 2 things to check when determining if an assignment of probabilities to
simple events is legitimate, 3 formulas for determining independence of events,
When to use median instead of mean, Physical interpretation of sample mean, Rule-of-thumb for
determining outliers, Statement of Chebyshev’s Theorem, Sample means and variances of linear
functions of data, Formula to use for P(A) if the outcomes in S are equally likely, When to use
the tree diagram (p. 39) to find probabilities, When to use the two-dimensional table (p. 42) to
find probabilities,