Mathematics

Statistics

Texas Essential Knowledge and Skills (TEKS) · TEKS 2012

44 standards
  • Mathematical process standards (1)
    • STAT.MATH.1.A

      Apply mathematics to problems arising in everyday life, society, and the workplace.

    • STAT.MATH.1.B

      Use a problem-solving model that incorporates analyzing given information, formulating a plan or strategy, determining a solution, justifying the solution, and evaluating the problem-solving process and the reasonableness of the solution.

    • STAT.MATH.1.C

      Select tools, including real objects, manipulatives, paper and pencil, and technology as appropriate, and techniques, including mental math, estimation, and number sense as appropriate, to solve problems; Page 28 October 2015 Update.

    • STAT.MATH.1.D

      Communicate mathematical ideas, reasoning, and their implications using multiple representations, including symbols, diagrams, graphs, and language as appropriate.

    • STAT.MATH.1.E

      Create and use representations to organize, record, and communicate mathematical ideas.

    • STAT.MATH.1.F

      Analyze mathematical relationships to connect and communicate mathematical ideas.

    • STAT.MATH.1.G

      Display, explain, or justify mathematical ideas and arguments using precise mathematical language in written or oral communication.

  • Statistical process sampling and experimentation (2)
    • STAT.MATH.2.A

      Compare and contrast the benefits of different sampling techniques, including random sampling and convenience sampling methods.

    • STAT.MATH.2.B

      Distinguish among observational studies, surveys, and experiments.

    • STAT.MATH.2.C

      Analyze generalizations made from observational studies, surveys, and experiments.

    • STAT.MATH.2.D

      Distinguish between sample statistics and population parameters.

    • STAT.MATH.2.E

      Formulate a meaningful question, determine the data needed to answer the question, gather the appropriate data, analyze the data, and draw reasonable conclusions.

    • STAT.MATH.2.F

      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 presentation.

    • STAT.MATH.2.G

      Critically analyze published findings for appropriateness of study design implemented, sampling methods used, or the statistics applied.

  • Variability (3)
    • STAT.MATH.3.A

      Distinguish between mathematical models and statistical models.

    • STAT.MATH.3.B

      Construct a statistical model to describe variability around the structure of a mathematical model for a given situation.

    • STAT.MATH.3.C

      Distinguish among different sources of variability, including measurement, natural, induced, and sampling variability.

    • STAT.MATH.3.D

      Describe and model variability using population and sampling distributions.

  • Categorical and quantitative data (4)
    • STAT.MATH.4.A

      Distinguish between categorical and quantitative data.

    • STAT.MATH.4.B

      Represent and summarize data and justify the representation.

    • STAT.MATH.4.C

      Analyze the distribution characteristics of quantitative data, including determining the possible existence and impact of outliers.

    • STAT.MATH.4.D

      Compare and contrast different graphical or visual representations given the same data set.

    • STAT.MATH.4.E

      Compare and contrast meaningful information derived from summary statistics given a data set.

    • STAT.MATH.4.F

      Analyze categorical data, including determining marginal and conditional distributions, using two-way tables. October 2015 Update Page 29 §111.C. High School.

  • Probability and random variables (5)
    • STAT.MATH.5.A

      Determine probabilities, including the use of a two-way table.

    • STAT.MATH.5.B

      Describe the relationship between theoretical and empirical probabilities using the Law of Large Numbers.

    • STAT.MATH.5.C

      Construct a distribution based on a technology-generated simulation or collected samples for a discrete random variable.

    • STAT.MATH.5.D

      Compare statistical measures such as sample mean and standard deviation from a technology-simulated sampling distribution to the theoretical sampling distribution.

  • Inference (6)
    • STAT.MATH.6.A

      Explain how a sample statistic and a confidence level are used in the construction of a confidence interval.

    • STAT.MATH.6.B

      Explain how changes in the sample size, confidence level, and standard deviation affect the margin of error of a confidence interval.

    • STAT.MATH.6.C

      Calculate a confidence interval for the mean of a normally distributed population with a known standard deviation.

    • STAT.MATH.6.D

      Calculate a confidence interval for a population proportion.

    • STAT.MATH.6.E

      Interpret confidence intervals for a population parameter, including confidence intervals from media or statistical reports.

    • STAT.MATH.6.F

      Explain how a sample statistic provides evidence against a claim about a population parameter when using a hypothesis test.

    • STAT.MATH.6.G

      Construct null and alternative hypothesis statements about a population parameter.

    • STAT.MATH.6.H

      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 situation.

    • STAT.MATH.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.

    • STAT.MATH.6.J

      Describe the potential impact of Type I and Type II Errors.

  • Bivariate data (7)
    • STAT.MATH.7.A

      Analyze scatterplots for patterns, linearity, outliers, and influential points.

    • STAT.MATH.7.B

      Transform a linear parent function to determine a line of best fit.

    • STAT.MATH.7.C

      Compare different linear models for the same set of data to determine best fit, including discussions about error.

    • STAT.MATH.7.D

      Compare different methods for determining best fit, including median-median and absolute value.

    • STAT.MATH.7.E

      Describe the relationship between influential points and lines of best fit using dynamic graphing technology.

    • STAT.MATH.7.F

      Identify and interpret the reasonableness of attributes of lines of best fit within the context, including slope and y-intercept.