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Mahomet-Seymour Schools

Curriculum

Mathematics - Statistics

 

Statistics

 

 

 

  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 self-selected 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, stem-and-leaf 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 non-mutually 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 p-value 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.

 

 

 

 

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