Statistics

Other Texas Mathematics sets

• Grade K
• Grade 1
• Grade 2
• Grade 3
• Grade 4
• Grade 5
• Grade 6
• Grade 7
• Algebra I (2012)
• Grade 8
• Algebra II
• Algebraic Reasoning
• Discrete Mathematics
• Grade 9
• Advanced Quantitative Reasoning
• Geometry (2012)
• Grades 10, 11, 12
• Independent Study in Mathematics
• Mathematical Models with Applications
• Precalculus

The student applies mathematical processes to apply understandings about statistical studies, surveys, and experiments to design and conduct a study and use graphical, numerical, and analytical techniques to communicate the results of the studyS.9-12.2

compare and contrast the benefits of different sampling techniques, including random sampling and convenience sampling methodsS.9-12.2.A

distinguish among observational studies, surveys, and experimentsS.9-12.2.B

analyze generalizations made from observational studies, surveys, and experimentsS.9-12.2.C

distinguish between sample statistics and population parametersS.9-12.2.D

formulate a meaningful question, determine the data needed to answer the question, gather the appropriate data, analyze the data, and draw reasonable conclusionsS.9-12.2.E

communicate methods used, analyses conducted, and conclusions drawn for a data-analysis project through the use of one or more of the following: a written report, a visual display, an oral report, or a multi-media presentationS.9-12.2.F

critically analyze published findings for appropriateness of study design implemented, sampling methods used, or the statistics appliedS.9-12.2.G

The student applies the mathematical process standards when describing and modeling variabilityS.9-12.3

distinguish between mathematical models and statistical modelsS.9-12.3.A

construct a statistical model to describe variability around the structure of a mathematical model for a given situationS.9-12.3.B

distinguish among different sources of variability, including measurement, natural, induced, and sampling variabilityS.9-12.3.C

describe and model variability using population and sampling distributionsS.9-12.3.D

The student applies the mathematical process standards to represent and analyze both categorical and quantitative dataS.9-12.4

distinguish between categorical and quantitative dataS.9-12.4.A

represent and summarize data and justify the representationS.9-12.4.B

analyze the distribution characteristics of quantitative data, including determining the possible existence and impact of outliersS.9-12.4.C

compare and contrast different graphical or visual representations given the same data setS.9-12.4.D

compare and contrast meaningful information derived from summary statistics given a data setS.9-12.4.E

analyze categorical data, including determining marginal and conditional distributions, using two-way tablesS.9-12.4.F

The student applies the mathematical process standards to connect probability and statisticsS.9-12.5

determine probabilities, including the use of a two-way tableS.9-12.5.A

describe the relationship between theoretical and empirical probabilities using the Law of Large NumbersS.9-12.5.B

construct a distribution based on a technology-generated simulation or collected samples for a discrete random variableS.9-12.5.C

compare statistical measures such as sample mean and standard deviation from a technology-simulated sampling distribution to the theoretical sampling distributionS.9-12.5.D

The student applies the mathematical process standards to make inferences and justify conclusions from statistical studiesS.9-12.6

explain how a sample statistic and a confidence level are used in the construction of a confidence intervalS.9-12.6.A

explain how changes in the sample size, confidence level, and standard deviation affect the margin of error of a confidence intervalS.9-12.6.B

calculate a confidence interval for the mean of a normally distributed population with a known standard deviationS.9-12.6.C

calculate a confidence interval for a population proportionS.9-12.6.D

interpret confidence intervals for a population parameter, including confidence intervals from media or statistical reportsS.9-12.6.E

explain how a sample statistic provides evidence against a claim about a population parameter when using a hypothesis testS.9-12.6.F

construct null and alternative hypothesis statements about a population parameterS.9-12.6.G

explain the meaning of the p-value in relation to the significance level in providing evidence to reject or fail to reject the null hypothesis in the context of the situationS.9-12.6.H

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 meansS.9-12.6.I

describe the potential impact of Type I and Type II ErrorsS.9-12.6.J

The student applies the mathematical process standards to analyze relationships among bivariate quantitative dataS.9-12.7

analyze scatterplots for patterns, linearity, outliers, and influential pointsS.9-12.7.A

transform a linear parent function to determine a line of best fitS.9-12.7.B

compare different linear models for the same set of data to determine best fit, including discussions about errorS.9-12.7.C

compare different methods for determining best fit, including median-median and absolute valueS.9-12.7.D

describe the relationship between influential points and lines of best fit using dynamic graphing technologyS.9-12.7.E

identify and interpret the reasonableness of attributes of lines of best fit within the context, including slope and y-interceptS.9-12.7.F