Determine likelihood that a hypothesis is reasonable

Determine likelihood that a hypothesis is reasonable

In this lesson you will learn to determine the likelihood that a hypothesis is reasonable by approximating a sampling distribution and analyzing the results.

ADDITIONAL MATERIALS

Lesson slides https://docs.google.com/presentation/d/1q81Y4duNL4HxNrgp0Dd84O-Abtjc9qvm/edit?usp=drivesdk&ouid=103344685123288532282&rtpof=true&sd=true

STANDARDS

CCSS.HSS-IC.B.4 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.

TEKS.S.6.I interpret the results of a hypothesis test using technology-generated results such as large sample tests for proportion, mean, difference between two proportions, and difference between two independent means; and

TEKS.S.6.E interpret confidence intervals for a population parameter, including confidence intervals from media or statistical reports;

IN.PS.DA.10 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.

IN.PS.DA.4 Understand hypothesis tests of means and differences between means and use them to reach conclusions. Compute and use confidence intervals to make estimates. Construct and interpret margin of error and confidence intervals for population proportions.

VA.IS.PS.17 The student, given data from a large sample, will determine and interpret appropriate point estimates and confidence intervals for parameters. The parameters will include proportion and mean, difference between two proportions, difference between two means (independent and paired), and slope of a least-squares regression line.

VA.DC.PS.10 The student will plan and conduct a well-designed experiment. The plan will address control, randomization, replication, blinding, and measurement of experimental error.

FL.MAFS.912.S-IC.2.4 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.

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