## Status message

Dear LOR user,

Thank you for being a big part of this community. To better support the initiatives around open educational resources in the state of Michigan, all resources on the Michigan Virtual Learning Object Repository (LOR) are being moved to #GoOpen Michigan on September 30th, 2018. During the transition, our LOR will be moved to an archived state, not allowing new user registration or new content to be added. An email with more details was sent to registered users of the LOR in September. To make use of the great resources on the platform, we encourage you to create an account and add your own new resources to the #GoOpen Michigan platform.

# Standards: Math

(1)
Use the rules of probability to compute probabilities of compound events in a uniform probability model.
Education Level: 9-12
Description:

Apply the general Multiplication Rule in a uniform probability model, P(A and B) = [P(A)]x[P(B|A)] =[P(B)]x[P(A|B)], and interpret the answer in terms of the model.*

(1)
Use the rules of probability to compute probabilities of compound events in a uniform probability model.
Education Level: 9-12
Description:

Use permutations and combinations to compute probabilities of compound events and solve problems.*

(1)
Understand and evaluate random processes underlying statistical experiments.
Education Level: 9-12
Description:

Understand statistics as a process for making inferences about population parameters based on a random sample from that population.*

(0)
Understand and evaluate random processes underlying statistical experiments.
Education Level: 9-12
Description:

Decide if a specified model is consistent with results from a given data-generating process, e.g., using simulation. For example, a model says a spinning coin falls heads up with probability 0. 5. Would a result of 5 tails in a row cause you to question the model?*

(1)
Make inferences and justify conclusions from sample surveys, experiments, and observational studies.
Education Level: 9-12
Description:

Recognize the purposes of and differences among sample surveys, experiments, and observational studies; explain how randomization relates to each.*

(0)
Make inferences and justify conclusions from sample surveys, experiments, and observational studies.
Education Level: 9-12
Description:

Use data from a sample survey to estimate a population mean or proportion; develop a margin of error through the use of simulation models for random sampling.*

(0)
Make inferences and justify conclusions from sample surveys, experiments, and observational studies.
Education Level: 9-12
Description:

Use data from a randomized experiment to compare two treatments; use simulations to decide if differences between parameters are significant.*

(0)
Make inferences and justify conclusions from sample surveys, experiments, and observational studies.
Education Level: 9-12
Description:

Evaluate reports based on data.*

(2)
Summarize, represent, and interpret data on a single count or measurement variable.
Education Level: 9-12
Description:

Represent data with plots on the real number line (dot plots, histograms, and box plots).*

(1)
Summarize, represent, and interpret data on a single count or measurement variable.
Education Level: 9-12
Description:

Use statistics appropriate to the shape of the data distribution to compare center (median, mean) and spread (interquartile range, standard deviation) of two or more different data sets.*

(0)
Summarize, represent, and interpret data on a single count or measurement variable.
Education Level: 9-12
Description:

Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers).*

(0)
Summarize, represent, and interpret data on a single count or measurement variable.
Education Level: 9-12
Description:

Use the mean and standard deviation of a data set to fit it to a normal distribution and to estimate population percentages. Recognize that there are data sets for which such a procedure is not appropriate. Use calculators, spreadsheets, and tables to estimate areas under the normal curve.*

(0)
Summarize, represent, and interpret data on two categorical and quantitative variables.
Education Level: 9-12
Description:

Summarize categorical data for two categories in two-way frequency tables. Interpret relative frequencies in the context of the data (including joint, marginal, and conditional relative frequencies). Recognize possible associations and trends in the data.*

(1)
Summarize, represent, and interpret data on two categorical and quantitative variables.
Education Level: 9-12
Description:

Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.*

(0)
Summarize, represent, and interpret data on two categorical and quantitative variables.
Education Level: 9-12
Description:

Fit a function to the data; use functions fitted to data to solve problems in the context of the data. Use given functions or choose a function suggested by the context. Emphasize linear, quadratic, and exponential models.*