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This course will review descriptive data techniques
and focus on statistical inference. Participants will apply techniques
to analyze data and prepare a project that illustrates sound statistical
reasoning. Access to a computer and the internet is required. A
laptop computer is recommended. Prerequisites: Math X465, Math
X 464A
REVIEW OF EXPLORATORY DATA ANALYSIS TECHNIQUES
(DATAREVIEW)
Participants use real-life numerical and categorical data sets
to review exploratory data analysis techniques. Participants use
the TI-83 and the Fathom™ statistical software as tools to
plot, summarize, and analyze data. Participants collect data about
their own students to prepare a statistical presentation based
on their findings.
USING NORMAL PROBABILITY MODELS (NORMAL)
Participants use data in context to review the Normal Probability
model. Participants convert the original units to standardized
deviations from the mean. Participants calculate the z-score and
determine the probability for an observation from a distribution
that is unimodal and symmetric.
SAMPLING AND CENTRAL LIMIT THEOREM
(SAMPLING)
Participants will learn various types of techniques for random
sampling. Participants will explore inferential statistics by using
estimates from a sample to test hypothesis about a population.
Participants will use a computer simulation to demonstrate the
central limit theorem.
INTRODUCING STATISTICAL INFERENCE THROUGH
CONFIDENCE INTERVALS (CONFIDENCE)
Participants revisit and use the information from the Four-Digit
Phone Numbers, the Reese’s Pieces®, and Body Temperature
Data investigations to construct confidence intervals by hand and
via the graphing calculator. Participants examine the relationship
between confidence intervals, margins of error, and the sizes of
samples. Participants interpret disclaimers found in surveys that
use confidence intervals and make conclusions about them.
HYPOTHESIS
TESTING (HYPOTHESIS)
Participants will use appropriate tests of hypotheses to check
claims made about the population.
BIVARIATE (PAIRED) DATA (BIVARIATE)
Participants use height and arm span data taken from a fifth grade
class to review graphing and interpretation techniques for univariate
data. Participants use the same data to learn how to plot bivariate
data, find the linear regression. Participants determine how well
the line predicts values for variables by making a residual plot.
Participants observe the distribution of bivariate data sets and
describe their graphs by shape, center, and spread. Participants
continue to use the TI-83 graphing calculator and Fathom™ software
to plot, summarize and analyze data.
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