The
learner will be able to distinguish between a population and a sample.
The
learner will be able to distinguish between a parameter and a statistic.
The
learner will be able to identify the level of measurement (nominal,
ordinal, interval, ratio) of a set of data.
The
learner will be able to recognize the importance of good sampling methods,
as well as the serious deficiency of poor sampling methods.
The
learner will be able to recognize that selfselected surveys cannot be used
to form valid conclusions about populations.
The
learner will be able to summarize data by constructing a frequency table or
relative frequency table.
The
learner will be able to visually display the nature of the distribution by
constructing a histogram, dot plot, stemandleaf plot, or pie chart.
The
learner will be able to calculate the measures of central tendency by
finding the mean, median, mode, and midrange.
The
learner will be able to calculate measures of variation by finding the
standard deviation, variance, and range.
The
learner will be able to use the Empirical Rule and Chebyshev’s Theorem.
The
learner will be able to calculate individual scores by using z scores,
quartiles, deciles or percentiles.
The
learner will be able to investigate and explore the spread of data, the center
of the data, and the range of values by constructing a box plot.
The
learner will be able to understand and interpret the results from tables,
graphs and stated measures.
The
learner will be able to use the Binomial Theorem to find the probability
for tossing coins.
The
learner will be able to find the probability for both dependent and
independent events.
The
learner will be able to find the probability for both mutually exclusive
and nonmutually exclusive events.
The
learner will be able to use scatter diagrams and the linear correlation
coefficient to decide whether there is a linear correlation between two
variables.
The
learner will be able to find the equation of the regression line which best
fits the paired data.
The
learner will be able to use and apply the normal distribution in context of
real situations.
The
learner will be able to use the normal distribution as an approximation of
the binomial distribution.
The
learner will be able to use the Central Limit Theorem to evaluate the
sample means of a population.
The
learner will be able to use the method: proof by contradiction and
hypothesis testing.
The
learner will be able to identify a null and alternative hypothesis.
The
learner will be able to use the pvalue test.
The
learner will use methods in statistics to evaluate a real life situation
with scores in a grade book.
The
learner will use methods in statistics to evaluate the normal distribution
of a real life sample.
