
Cobb County School District 
Mathematics (Updated July 2004) 
Mathematics  Statistics 
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Goals and Descriptions 

Data Analysis and Probability

PS1: DATA ORGANIZATION: FORMULATE
The learner will be able to
formulate studies to answer question to realworld situations.


M.STAT.1.1 Sampling: Concepts
The learner will be able to
distinguish between sample and population, identify characteristics of representative samples to minimize bias and error, and recognize the variability among repeated samples taken from the same population.
Bloom's 
Scope 
Hours 
Source 
Application 
Master 
2.0 
GA: Quality Core Curriculum, December 2000, Statistics, #8 


M.STAT.1.2 Statistical Analysis: Estimate
The learner will be able to
develop the concept of estimating population parameters using confidence intervals produced from comparisons of box plots, and apply the capturerecapture model to generate a confidence interval for the populations.
Bloom's 
Scope 
Hours 
Source 
Application 
Master 
3.0 
GA: Quality Core Curriculum, December 2000, Statistics, #22 


M.STAT.1.3 Statistics: Models
The learner will be able to
develop estimates (both point and interval) for parameters (such as mean, standard deviation and proportion of successes) and test hypotheses concerning these parameters through the using appropriate statistical models.
Bloom's 
Scope 
Hours 
Source 
Synthesis 
Master 
2.0 
GA: Quality Core Curriculum, December 2000, Statistics, #24 


M.STAT.1.4 Sampling: \Construct
The learner will be able to
construct sampling distributions from binomial populations construct student experiments, random number tables and computer simulations.
Bloom's 
Scope 
Hours 
Source 
Analysis 
Master 
2.0 
GA: Quality Core Curriculum, December 2000, Statistics, #20 


M.STAT.1.5 Mathematical Modeling: Simulation
The learner will be able to
use the eight step process to build a model for simulating a given practical problem situation and use manipulatives, random number generators, calculators, and/or computers to perform the simulation to form an approximation to the problem solution.
Bloom's 
Scope 
Hours 
Source 
Synthesis 
Master 
8.0 
GA: Quality Core Curriculum, December 2000, Statistics, #14 


M.STAT.1.6 Sampling: Concepts
The learner will be able to
understand the concept of randomness as applied to sample selection and identify other sampling methods suitable to given situations.
Bloom's 
Scope 
Hours 
Source 
Analysis 
Master 
1.0 
GA: Quality Core Curriculum, December 2000, Statistics, #9 


M.STAT.1.7 Data Collection: Methods
The learner will be able to
design a survey or an opinion poll or choose other methods of data to solve problems.
Bloom's 
Scope 
Hours 
Source 
Synthesis 
Master 
1.0 
GA: Quality Core Curriculum, December 2000, Statistics, #10 

PS2: DATA ORGANIZATION: CONDUCT
The learner will be able to
conduct investigations using statistical tools and display resulting data.


M.STAT.2.1 Data: Organize/Summarize/Characterize
The learner will be able to
organize, summarize, characterize, and interpret data from practical situations using relevant data sets by constructing of tables, graphs, and charts including frequency distributions, histograms, line plots, stemandleaf plots, box plots, and/or scatterplots for bivariate data.
Bloom's 
Scope 
Hours 
Source 
Synthesis 
Master 
3.0 
GA: Quality Core Curriculum, December 2000, Statistics, #1 


M.STAT.2.2 Sampling: Create
The learner will be able to
construct and interpret 90% and 95% box plots for various size samples, and use the box plots to summarize the sampling distribution.
Bloom's 
Scope 
Hours 
Source 
Analysis 
Master 
1.0 
GA: Quality Core Curriculum, December 2000, Statistics, #21 


M.STAT.2.3 Central Limit Theorem: Use
The learner will be able to
apply the Central Limit Theorem and understand its impact on the distribution of the sample mean, including the effects of sample size.
Bloom's 
Scope 
Hours 
Source 
Application 
Master 
2.0 
GA: Quality Core Curriculum, December 2000, Statistics, #23 


M.STAT.2.4 Data Collection: Experimental
The learner will be able to
collect and analyze data using experimental models and random number tables and generators.
Bloom's 
Scope 
Hours 
Source 
Analysis 
Master 
2.0 
GA: Quality Core Curriculum, December 2000, Statistics, #11 


M.STAT.2.5 Simulations: Perform
The learner will be able to
perform simulations for problems where the probability of success is onehalf and other then onehalf and perform simulations for situations with an unknown number of key components.
Bloom's 
Scope 
Hours 
Source 
Synthesis 
Master 
4.0 
GA: Quality Core Curriculum, December 2000, Statistics, #15 

PS3: DATA ANALYSIS: CENTRAL TENDENCY
The learner will be able to
analyze realworld data collected using appropriate measures of central tendency and dispersion.


M.STAT.3.1 Variation: Analyze Source
The learner will be able to
analyze sources of variation and interpret and draw conclusions when solving applied problems. (Some may include the difference between samples and populations, sampling variability, the application of probability to make generalizations and predictions about populations based on the analysis of samples, the concept of random or chance variation, and analysis of variance).
Bloom's 
Scope 
Hours 
Source 
Analysis 
Develop 
4.0 
GA: Quality Core Curriculum, December 2000, Statistics, #28 


M.STAT.3.2 Data Analysis: Summarize
The learner will be able to
apply the measures of central tendency (mean, median, and mode), and measures of spread ( range, interquartile range, and standard deviation).
Bloom's 
Scope 
Hours 
Source 
Comprehension 
Master 
1.0 
GA: Quality Core Curriculum, December 2000, Statistics, #2 


M.STAT.3.3 Data Analysis: Recognize/Trends
The learner will be able to
identify trends in data represented graphically, including patterns, clusters, and outliers.
Bloom's 
Scope 
Hours 
Source 
Knowledge 
Master 
1.0 
GA: Quality Core Curriculum, December 2000, Statistics, #3 


M.STAT.3.4 Statistical Analysis: Alternative
The learner will be able to
apply distributionfree or nonparametric methods as alternative to statistical analyses that make assumptions about populations sampled. (Applications from practical problems can be presented using such measures as the sign test, the MannWhitney U test and Sperman's rank correlation test).
Bloom's 
Scope 
Hours 
Source 
Analysis 
Introduce 
5.0 
GA: Quality Core Curriculum, December 2000, Statistics, #25 

PS4: DATA ANALYSIS: EVALUATE
The learner will be able to
evaluate statistical studies and determine inferences that can be justified.


M.STAT.4.1 Data: Analyze Bivariate
The learner will be able to
analyze bivariate data represented graphically and predict results by fitting a line to the data, using methods such as mean fit and least squares and tools such as computers and calculators.
Bloom's 
Scope 
Hours 
Source 
Analysis 
Master 
4.0 
GA: Quality Core Curriculum, December 2000, Statistics, #4 


M.STAT.4.2 Correlation: Compute/Investigate
The learner will be able to
for a given bivariate scatter plot or data set, characterizes the correlation, calculates the correlation coefficient, and determine if a linear relationship exists.
Bloom's 
Scope 
Hours 
Source 
Analysis 
Master 
2.0 
GA: Quality Core Curriculum, December 2000, Statistics, #5 


M.STAT.4.3 Data: Linear Transformation
The learner will be able to
understand the effect of linear transformations have on the analysis and exploration of data.
Bloom's 
Scope 
Hours 
Source 
Analysis 
Master 
1.0 
GA: Quality Core Curriculum, December 2000, Statistics, #6 


M.STAT.4.4 Data Analysis: Interpret Out
The learner will be able to
interpret the outcome of data analysis and communicate these results.
Bloom's 
Scope 
Hours 
Source 
Analysis 
Master 
1.0 
GA: Quality Core Curriculum, December 2000, Statistics, #12 


M.STAT.4.5 Statistics: Proper/Improper
The learner will be able to
identify sound examples of statistics in decision making and correct the misuses of statistics.
Bloom's 
Scope 
Hours 
Source 
Analysis 
Master 
1.0 
GA: Quality Core Curriculum, December 2000, Statistics, #7 


M.STAT.4.6 Proof: Use/Mathematical Induction
The learner will be able to
use mathematical induction the derivation of certain formulas, the verification of appropriate properties, proofs of equivalence, and deductive reasoning.
Bloom's 
Scope 
Hours 
Source 
Synthesis 
Introduce 
2.0 
GA: Quality Core Curriculum, December 2000, Statistics, #27 

PS5: PROBABILITY: COUNTING PRINCIPLES
The learner will be able to
apply counting principles in real world contexts.


M.STAT.5.1 Experiments: Apply Results
The learner will be able to
use studentgenerate data sets, games of chance, manipulatives, and historic data to estimate probabilities with the empirical approach. Apply the results obtained from active experiments to illustrate the Law of Large Numbers and to develop the concept of theoretical probability.
Bloom's 
Scope 
Hours 
Source 
Analysis 
Master 
4.0 
GA: Quality Core Curriculum, December 2000, Statistics, #13 


M.STAT.5.2 Counting Methods: Apply
The learner will be able to
apply counting techniques and calculate the probability of the union and the intersection of two events, the probability of the complement, and conditional probability.
Bloom's 
Scope 
Hours 
Source 
Application 
Master 
2.0 
GA: Quality Core Curriculum, December 2000, Statistics, #16 

PS6: PROBABILITY
The learner will be able to
apply the laws of probability in real world contexts.


M.STAT.6.1 Probability: Find/Odds/For/Associated
The learner will be able to
distinguish between odds for and probabilities and find the odds associated with given events.
Bloom's 
Scope 
Hours 
Source 
Application 
Master 
1.0 
GA: Quality Core Curriculum, December 2000, Statistics, #17 


M.STAT.6.2 Probability: Assign
The learner will be able to
assigns probabilities to the outcomes of a random variable and calculate expected value.
Bloom's 
Scope 
Hours 
Source 
Application 
Master 
1.5 
GA: Quality Core Curriculum, December 2000, Statistics, #18 


M.STAT.6.3 Probability Distributions: Distinguish
The learner will be able to
distinguishes between discrete and continuous distributions and solves problems using probability distributions, including binomial, normal, Poisson, and chi square.
Bloom's 
Scope 
Hours 
Source 
Application 
Master 
3.0 
GA: Quality Core Curriculum, December 2000, Statistics, #19 


M.STAT.6.4 Probability: Geometric
The learner will be able to
use geometric probability to develop problem solving skills through experiments whose outcomes can be represented by points in a geometric region.
Bloom's 
Scope 
Hours 
Source 
Synthesis 
Master 
3.0 
GA: Quality Core Curriculum, December 2000, Statistics, #26 

2003 Cobb County School
District. All Rights Reserved
514 Glover Street  Marietta, Ga. 30060  (770) 4263300
Send your comments to Sue Brown
visitors since July 31, 2004
