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1 | Key Concepts | Standards | Description | Q1 | Q2 | Q3 | Q4 | ||||||||||||||||||
2 | PS.SPCR.1 | Describe events as subsets of a sample space and a. Use Venn diagrams to represent intersections, unions, and complements. b. Relate intersections, unions, and complements to the words and, or, and not. c. Represent sample spaces for compound events using Venn diagrams. | |||||||||||||||||||||||
3 | PS.SPCR.2 | Use the multiplication rule to calculate probabilities for independent and dependent events. Understand that two events A and B are independent if the probability of A and B occurring together is the product of their probabilities and use this characterization to determine if they are independent. | |||||||||||||||||||||||
4 | PS.SPCR.3 | Understand the conditional probability of A given B as P(A and B)/P(B), and interpret independence of A and B as saying that the conditional probability of A given B is the same as the probability of A, and the conditional probability of B given A is the same as the probability of B. | |||||||||||||||||||||||
5 | PS.SPCR.4 | Construct and interpret two-way frequency tables of data when two categories are associated with each object being classified. Use the two-way table as a sample space to decide if events are independent and to approximate conditional probabilities. | |||||||||||||||||||||||
6 | PS.SPCR.5 | Recognize and explain the concepts of conditional probability and independence in everyday language and everyday situations. | |||||||||||||||||||||||
7 | PS.SPCR.6 | Calculate the conditional probability of an event A given event B as the fraction of B’s outcomes that also belong to A and interpret the answer in terms of the model. | |||||||||||||||||||||||
8 | PS.SPCR.7 | Apply the Addition Rule and the Multiplication Rule to determine probabilities, including conditional probabilities, and interpret the results in terms of the probability model. | |||||||||||||||||||||||
9 | PS.SPCR.8 | Apply the Addition Rule and the Multiplication Rule to determine probabilities, including conditional probabilities, and interpret the results in terms of the probability model. | |||||||||||||||||||||||
10 | Making Inferences and Justifying Conclusions | PS.SPMJ.1* | Understand statistics and sampling distributions as a process for making inferences about population parameters based on a random sample from that population. | ||||||||||||||||||||||
11 | PS.SPMJ.2* | Distinguish between experimental and theoretical probabilities. Collect data on a chance event and use the relative frequency to estimate the theoretical probability of that event. Determine whether a given probability model is consistent with experimental results. | |||||||||||||||||||||||
12 | PS.SPMJ.3 | Plan and conduct a survey to answer a statistical question. Recognize how the plan addresses sampling technique, randomization, measurement of experimental error and methods to reduce bias. | |||||||||||||||||||||||
13 | PS.SPMJ.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. | |||||||||||||||||||||||
14 | PS.SPMJ.5 | Distinguish between experiments and observational studies. Determine which of two or more possible experimental designs will best answer a given research question and justify the choice based on statistical significance. | |||||||||||||||||||||||
15 | PS.SPMJ.6 | Evaluate claims and conclusions in published reports or articles based on data by analyzing study design and the collection, analysis, and display of the data. | |||||||||||||||||||||||
16 | Interpreting Data | PS.SPID.1* | Select and create an appropriate display, including dot plots, histograms, and box plots, for data that includes only real numbers. | ||||||||||||||||||||||
17 | PS.SPID.1* | Use statistics appropriate to the shape of the data distribution to compare center and spread of two or more different data sets that include all real numbers. | |||||||||||||||||||||||
18 | PS.SPID.3* | Summarize and represent data from a single data set. Interpret differences in shape, center, and spread in the context of the data set, accounting for possible effects of extreme data points (outliers). | |||||||||||||||||||||||
19 | PS.SPID.4 | 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. | |||||||||||||||||||||||
20 | PS.SPID.5* | Analyze bivariate categorical data using two-way tables and identify possible associations between the two categories using marginal, joint, and conditional frequencies. | |||||||||||||||||||||||
21 | PS.SPID.6* | Using technology, create scatterplots and analyze those plots to compare the fit of linear, quadratic, or exponential models to a given data set. Select the appropriate model, fit a function to the data set, and use the function to solve problems in the context of the data. | |||||||||||||||||||||||
22 | PS.SPID.7* | Find linear models using median fit and regression methods to make predictions. Interpret the slope and intercept of a linear model in the context of the data. | |||||||||||||||||||||||
23 | PS.SPID.8* | Compute using technology and interpret the correlation coefficient of a linear fit. | |||||||||||||||||||||||
24 | PS.SPID.9 | Differentiate between correlation and causation when describing the relationship between two variables. Identify potential lurking variables which may explain an association between two variables. | |||||||||||||||||||||||
25 | PS.SPID.10 | Create residual plots and analyze those plots to compare the fit of linear, quadratic, and exponential models to a given data set. Select the appropriate model and use it for interpolation. | |||||||||||||||||||||||
26 | Using Probability to Make Decisions | PS.PMD.1 | Develop the probability distribution for a random variable defined for a sample space in which a theoretical probability can be calculated and graph the distribution. | ||||||||||||||||||||||
27 | PS.PMD.2 | Calculate the expected value of a random variable as the mean of its probability distribution. Find expected values by assigning probabilities to payoff values. Use expected values to evaluate and compare strategies in real-world scenarios. | |||||||||||||||||||||||
28 | PS.PMD.3 | Construct and compare theoretical and experimental probability distributions and use those distributions to find expected values. | |||||||||||||||||||||||
29 | PS.PMD.4* | Use probability to evaluate outcomes of decisions by finding expected values and determine if decisions are fair. | |||||||||||||||||||||||
30 | PS.PMD.5* | Use probability to evaluate outcomes of decisions. Use probabilities to make fair decisions. | |||||||||||||||||||||||
31 | PS.PMD.6* | Analyze decisions and strategies using probability concepts. | |||||||||||||||||||||||
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