AP Statistics Sample Audit Syllabus
AP Statistics SyllabusBexley High SchoolCOURSE DESCRIPTION:AP Statistics is the high school equivalent of a one semester, introductory college statisticscourse. In this course, students develop strategies for collecting, organizing, analyzing, anddrawing conclusions from data. Students design, administer, and tabulate results from surveysand experiments. Probability and simulations aid students in constructing models for chancebehavior. Sampling distributions provide the logical structure for confidence intervals andhypothesis tests. Students use a TI-83/84 graphing calculator, Fathom and Minitab statisticalsoftware, and Web-based java applets to investigate statistical concepts. To develop effectivestatistical communication skills, students are required to prepare frequent written and oralanalyses of real data.COURSE GOALS:In AP Statistics, students are expected to learnSkills To produce convincing oral and written statistical arguments, using appropriateterminology, in a variety of applied settings. When and how to use technology to aid them in solving statistical problemsKnowledge Essential techniques for producing data (surveys, experiments, observational studies),analyzing data (graphical & numerical summaries), modeling data (probability, randomvariables, sampling distributions), and drawing conclusions from data (inferenceprocedures – confidence intervals and significance tests)Habits of mind To become critical consumers of published statistical results by heightening theirawareness of ways in which statistics can be improperly used to mislead, confuse, ordistort the truth.COURSE OUTLINE:Text: The Practice of Statistics (4th edition), by Starnes, Yates, and Moore, W. H. Freeman &Co., 2010.1
Chapter 1Day1TopicsChapter 1 Introduction; Activity:Hiring discrimination: This activitymodels the components of thestatistical problem solving process:research question, data analysis,probability model, and inferenceObjectives: Students will be able to 21.1 Bar Graphs and Pie Charts,Graphs: Good and Bad 31.1 Two-Way Tables and MarginalDistributions, RelationshipsBetween Categorical Variables:Conditional Distributions,Organizing a Statistical Problem,Technology: Analyzing Two-WayTables with Minitab 41.1 Two-Way Tables and MarginalDistributions, RelationshipsBetween Categorical Variables:Conditional Distributions,Organizing a Statistical Problem,Technology: Analyzing Two-WayTables with Minitab 51.2 Dotplots, Describing Shape,Comparing Distributions, Stemplots 61.2 Histograms, Using HistogramsWisely, Technology: MakingHistograms on the Calculator 71.2 Histograms, Using HistogramsWisely, Technology: MakingHistograms on the Calculator Identify the individuals and variables in a setof data.Classify variables as categorical orquantitative. Identify units of measurementfor a quantitative variable.Make a bar graph of the distribution of acategorical variable or, in general, tocompare related quantities.Recognize when a pie chart can and cannotbe used.Identify what makes some graphs deceptive.From a two-way table of counts, answerquestions involving marginal and conditionaldistributions.Describe the relationship between twocategorical variables in context bycomparing the appropriate conditionaldistributions.Construct bar graphs to display therelationship between two categoricalvariables.From a two-way table of counts, answerquestions involving marginal and conditionaldistributions.Describe the relationship between twocategorical variables in context bycomparing the appropriate conditionaldistributions.Construct bar graphs to display therelationship between two categoricalvariables.Make a dotplot or stemplot to display smallsets of data.Describe the overall pattern (shape, center,spread) of a distribution and identify anymajor departures from the pattern (likeoutliers).Identify the shape of a distribution from adotplot, stemplot, or histogram as roughlysymmetric or skewed. Identify the number ofmodes.Make a histogram with a reasonable choiceof classes.Identify the shape of a distribution from adotplot, stemplot, or histogram as roughlysymmetric or skewed. Identify the number ofmodes.Interpret histograms.Make a histogram with a reasonable choiceof classes.Identify the shape of a distribution from adotplot, stemplot, or histogram as roughlysymmetric or skewed. Identify the number ofmodes.Homeworkp.7-8 # 1, 3,5, 7, 8p.22-24#11,13,15,17p.24 #19,21,23p. 25-26#25, 27-32p.42-44#37, 39, 41,43, 45, 47p.45-47#53, 55, 57p.47-49#59, 60,69-742
8910111.3 Measuring Center: Mean andMedian, Comparing Mean andMedian, Measuring Spread: IQR,Identifying Outliers1.3 Measuring Center: Mean andMedian, Comparing Mean andMedian, Measuring Spread: IQR,Identifying Outliers1.3 Five Number Summary andBoxplots, Measuring Spread:Standard Deviation, ChoosingMeasures of Center and Spread,Technology: Making Boxplots onthe Calculator, ComputingNumerical Summaries with Minitaband the Calculator1.3 Five Number Summary andBoxplots, Measuring Spread:Standard Deviation, ChoosingMeasures of Center and Spread,Technology: Making Boxplots onthe Calculator, ComputingNumerical Summaries with Minitaband the Calculator12Chapter 1 Review13Chapter 1 Test Interpret histograms. Calculate and interpret measures of center(mean, median) in contextCalculate and interpret measures of spread(IQR) in contextIdentify outliers using the 1.5 IQR rule.Calculate and interpret measures of center(mean, median) in contextCalculate and interpret measures of spread(IQR) in contextIdentify outliers using the 1.5 IQR rule.Make a boxplot.Calculate and interpret measures of spread(standard deviation)Select appropriate measures of center andspreadUse appropriate graphs and numericalsummaries to compare distributions ofquantitative variables.Make a boxplot.Calculate and interpret measures of spread(standard deviation)Select appropriate measures of center andspreadUse appropriate graphs and numericalsummaries to compare distributions ofquantitative variables. p.70 #79,81, 83p.70-71# 87, 89p.71-72#91, 93, 95p.72-74#97, 103,105, 107110Chapter 1ReviewExercisesChapter 1 Project: Critical statistical analysis – each student collects data and analyzes itusing the techniques learned in this unit and prepares a written analysis. Evaluation using afour-point rubric like the AP Free Response questions.3
Chapter 2DayTopics 12.1 Introduction, Measuring Position:Percentiles, Cumulative RelativeFrequency Graphs, MeasuringPosition: z-scores 22.1 Introduction, Measuring Position:Percentiles, Cumulative RelativeFrequency Graphs, MeasuringPosition: z-scores 32.1 Transforming Data, DensityCurves 42.1 Transforming Data, DensityCurves 52.2 Normal Distributions, The 68-9599.7 Rule, The Standard NormalDistribution, Technology: StandardNormal Curve Calculations with theCalculator and with an Applet 62.2 Normal Distributions, The 68-9599.7 Rule, The Standard NormalDistribution, Technology: StandardNormal Curve Calculations with theCalculator and with an Applet 782.2 Normal Distribution Calculations,Technology: Normal CurveCalculations with the Calculator andwith an Applet2.2 Normal Distribution Calculations,Technology: Normal CurveCalculations with the Calculator andwith an AppletObjectives: Students will be able to Use percentiles to locate individual valueswithin distributions of data.Interpret a cumulative relative frequencygraph.Find the standardized value (z-score) of anobservation. Interpret z-scores in context.Use percentiles to locate individual valueswithin distributions of data.Interpret a cumulative relative frequencygraph.Find the standardized value (z-score) of anobservation. Interpret z-scores in context.Describe the effect of adding, subtracting,multiplying by, or dividing by a constant onthe shape, center, and spread of adistribution of data.Approximately locate the median (equalareas point) and the mean (balance point) ona density curve.Describe the effect of adding, subtracting,multiplying by, or dividing by a constant onthe shape, center, and spread of adistribution of data.Approximately locate the median (equalareas point) and the mean (balance point) ona density curve.Use the 68–95–99.7 rule to estimate thepercent of observations from a Normaldistribution that fall in an interval involvingpoints one, two, or three standard deviationson either side of the mean.Use the standard Normal distribution tocalculate the proportion of values in aspecified interval.Use the standard Normal distribution todetermine a z-score from a percentile.Use the 68–95–99.7 rule to estimate thepercent of observations from a Normaldistribution that fall in an interval involvingpoints one, two, or three standard deviationson either side of the mean.Use the standard Normal distribution tocalculate the proportion of values in aspecified interval.Use the standard Normal distribution todetermine a z-score from a percentile.Homeworkp.105-106#5, 7, 9p.106-107#11, 13, 15p.107-108#19, 21, 23p.108-109#31, 33-38p.131#41, 43, 45p.131-132#47, 49, 51 Use Table A to find the percentile of a valuefrom any Normal distribution and the valuethat corresponds to a given percentile.p.132# 53, 55 Use Table A to find the percentile of a valuefrom any Normal distribution and the valuethat corresponds to a given percentile.p.132-133#57, 594
92.2 Assessing Normality, NormalProbability Plots on the Calculator 10Chapter 2 Review11Chapter 2 TestMake an appropriate graph to determine if adistribution is bell-shaped.Use the 68-95-99.7 rule to assess Normalityof a data set.Interpret a Normal probability plotp.133-135#63, 65,66, 68, 6974Chapter 2ReviewExercises39R, 40R,75R, 76R5
Chapter 3DayTopics 12345Chapter 3 Introduction, Activity: CSIStats, 3.1 Explanatory andresponse variables, Displayingrelationships: scatterplots,Interpreting scatterplots,Technology: Scatterplots on theCalculator3.1 Measuring linear association:correlation, Facts about correlation,Technology: Correlation andRegression Applet3.1 Measuring linear association:correlation, Facts about correlation,Technology: Correlation andRegression Applet 3.2 Least-squares regression,Interpreting a regression line,Prediction, Technology: LeastSquares Regression Lines on theCalculator 3.2 Residuals and the least-squaresregression line, Calculating theequation of the least-squaresregression line, Technology:Residual Plots and s on theCalculator 63.2 Residuals and the least-squaresregression line, Calculating theequation of the least-squaresregression line, Technology:Residual Plots and s on theCalculator 73.2 How well the line fits the data:residual plots, How well the line fitsthe data: the role of r2 in regression Objectives: Students will be able to Describe why it is important to investigaterelationships between variables.Identify explanatory and responsevariables in situations where one variablehelps to explain or influences the other.Make a scatterplot to display therelationship between two quantitativevariables.Describe the direction, form, and strengthof the overall pattern of a scatterplot.Recognize outliers in a scatterplot.Know the basic properties of correlation.Calculate and interpret correlation incontext.Explain how the correlation r is influencedby extreme observations.Know the basic properties of correlation.Calculate and interpret correlation incontext.Explain how the correlation r is influencedby extreme observations.Interpret the slope and y intercept of aleast-squares regression line in context.Use the least-squares regression line topredict y for a given x.Explain the dangers of extrapolation.Calculate and interpret residuals incontext.Explain the concept of least squares.Use technology to find a least-squaresregression line.Find the slope and intercept of the leastsquares regression line from the meansand standard deviations of x and y andtheir correlation.Calculate and interpret residuals incontext.Explain the concept of least squares.Use technology to find a least-squaresregression line.Find the slope and intercept of the leastsquares regression line from the meansand standard deviations of x and y andtheir correlation.Construct and interpret residual plots toassess if a linear model is appropriate.Use the standard deviation of the residualsto assess how well the line fits the data.Use r2 to assess how well the line fits thedata.Interpret the standard deviation of theresiduals and r2 in context.Homeworkp.158-160#1, 5, 7,11, 13p.160-161#14–18p.161-163#21, 26,27–32p.191#35, 37,39, 41p.191-192#43, 45p.192-193#47, 53p.192-193#49, 54, 566
83.2 How well the line fits the data:residual plots, How well the line fitsthe data: the role of r2 in regression 93.2 Interpreting computerregression output, Correlation andregression wisdom, Technology:Least-Squares Regression usingMinitab and JMP 103.2 Interpreting computerregression output, Correlation andregression wisdom, Technology:Least-Squares Regression usingMinitab and JMP11Chapter 3 Review12Chapter 3 Test Construct and interpret residual plots toassess if a linear model is appropriate.Use the standard deviation of the residualsto assess how well the line fits the data.Use r2 to assess how well the line fits thedata.Interpret the std dev of the residuals and r2.Identify the equation of a least-squaresregression line from computer output.Explain why association doesn’t implycausation.Recognize how the slope, y intercept,standard deviation of the residuals, and r2are influenced by extreme observations.Identify the equation of a least-squaresregression line from computer output.Explain why association doesn’t implycausation.Recognize how the slope, y intercept,standard deviation of the residuals, and r2are influenced by extreme observations.p.193-194#58–61p.194-196#63, 65, 68p.196-197#69, 71–78ChapterReviewExercises33R, 34R, 79R,80R, 81R7
Chapter 4Day1Topics4.1 Introduction, Sampling andSurveys, How to Sample Badly,How to Sample Well: RandomSamples, Technology: Choosingan SRS using an Applet orCalculator 24.1 Other Sampling Methods 34.1 Other Sampling Methods44.1 Inference for Sampling,Sample Surveys: What Can GoWrong? 54.2 Observational Studies vs.Experiments, The Language ofExperiments, How to ExperimentBadly 64.2 Observational Studies vs.Experiments, The Language ofExperiments, How to ExperimentBadly 74.2 How to Experiment Well,Three Principles of ExperimentalDesign 84.2 Experiments: What Can GoWrong? Inference for Experiments 94.2 Blocking, Matched PairsDesign Objectives: Students will be able to Identify the population and sample in asample survey.Identify voluntary response samples andconvenience samples. Explain how thesebad sampling methods can lead to bias.Describe how to use Table D to select asimple random sample (SRS).Distinguish a simple random sample from astratified random sample or cluster sample.Give advantages and disadvantages of eachsampling method.Distinguish a simple random sample from astratified random sample or cluster sample.Give advantages and disadvantages of eachsampling method.Explain how undercoverage, nonresponse,and question wording can lead to bias in asample survey.Distinguish between an observational studyand an experiment.Explain how a lurking variable in anobservational study can lead toconfounding.Identify the experimental units or subjects,explanatory variables (factors), treatments,and response variables in an experiment.Distinguish between an observational studyand an experiment.Explain how a lurking variable in anobservational study can lead toconfounding.Identify the experimental units or subjects,explanatory variables (factors), treatments,and response variables in an experiment.Describe a completely randomized designfor an experiment.Explain why random assignment is animportant experimental design principle.Describe how to avoid the placebo effect inan experiment.Explain the meaning and the purpose ofblinding in an experiment.Explain in context what “statisticallysignificant” means.Distinguish between a completelyrandomized design and a randomized blockdesign.Know when a matched pairs experimentaldesign is appropriate and how to implementsuch a design.Homeworkp.226-226#1, 3,5,7,9, 11p.227-228#17, 19, 21p.228-229#23, 25,27,28p.229#29, 31,33, 35p.230 #3742,&p.253#45, 47p.253-254#49, 51, 53p.254-256#57, 63,65, 67p.256-257#69,71,73,75*(*We willanalyze thisdata again inan Activity inchapter 10)p.257-258#77, 79, 818
1011124.2 Blocking, Matched PairsDesign4.3 Scope of Inference, theChallenges of EstablishingCausation4.2 Class Experimentsor4.3 Data Ethics* (*optional topic)13Chapter 4 Review14Chapter 4 TestDistinguish between a completelyrandomized design and a randomized blockdesign.Know when a matched pairs experimentaldesign is appropriate and how to implementsuch a design.p.259-260#85, 91-98 Determine the scope of inference for astatistical study.p.269# 102-108 Evaluate whether a statistical study hasbeen carried out in an ethical manner.55, 83, 87, 89 Chapter 4ReviewExercisesPart 1:CumulativeAP ReviewExercises9
Chapter 5Day12Topics5.1 Introduction, The Idea ofProbability, Myths aboutRandomness5.1 Simulation, Technology:Random Numbers with Calculators35.2 Probability Models, Basic Rulesof Probability45.2 Two-Way Tables andProbability, Venn Diagrams andProbability55.2 Two-Way Tables andProbability, Venn Diagrams andProbability Objectives: Students will be able to Interpret probability as a long-run relativefrequency in context. Use simulation to model chance behavior. Describe a probability model for a chanceprocess.Use basic probability rules, including thecomplement rule and the addition rule formutually exclusive events.Use a Venn diagram to model a chanceprocess involving two events.Use the general addition rule to calculateP(A B)Use a Venn diagram to model a chanceprocess involving two events.Use the general addition rule to calculateP(A B)When appropriate, use a tree diagram todescribe chance behavior.Use the general multiplication rule to solveprobability questions.Determine whether two events areindependent.Find the probability that an event occursusing a two-way table.When appropriate, use a tree diagram todescribe chance behavior.Use the general multiplication rule to solveprobability questions.Determine whether two events areindependent.Find the probability that an event occursusing a two-way table.When appropriate, use the multiplicationrule for independent events to computeprobabilities.Compute conditional probabilities.When appropriate, use the multiplicationrule for independent events to computeprobabilities.Compute conditional probabilities. 65.3 What is ConditionalProbability?, Conditional Probabilityand Independence, Tree Diagramsand the General Multiplication Rule 75.3 What is ConditionalProbability?, Conditional Probabilityand Independence, Tree Diagramsand the General Multiplication Rule 895.3 Independence: A SpecialMultiplication Rule, CalculatingConditional Probabilities5.3 Independence: A SpecialMultiplication Rule, CalculatingConditional Probabilities10Review1
3.2 Least-squares regression, Interpreting a regression line, Prediction, Technology: Least-Squares Regression Lines on the Calculator Interpret the slope and y intercept of a least-squares regression line in context. Use the least-squares regression line to predict y f
The quality audit system is mainly classified in three different categories: i Internal Audit ii. External Audits iii. Regulatory Audit . Types Of Quality Audit. In food industries all three audit system may be used to carry out 1. Product manufacturing audit 2. Plant sanitation/GMP audit 3. Product Quality audit 4. HACCP audit
posts by the due date. There is no make-up for quizzes (instead, I will drop two lowest grades). For exams, make-ups will be considered only for legitimate reasons with proper documentation. THIS IS A SAMPLE SYLLABUS - Current course syllabus is available within Canvas SAMPLE Syllabus SAMPLE Syllabus SAMPLE Syllabus Syllabus
INTERNAL AUDIT Example –Internal audit report [Short Client Name] Internal Audit Report Rev. [Rev Number] STEP ONE: Audit Plan Process to Audit (Audit Scope): Audit Date(s): Lead Auditor: Audit #: Auditor(s): Site(s) to Audit: Applicable Clauses of [ISO 9001 or AS9100] S
4.1 Quality management system audit 9.2.2.2 Quality management system audit - except: organization shall audit to verify compliance with MAQMSR, 2nd Ed. 4.2 Manufacturing process audit 9.2.2.3 Manufacturing process audit 4.3 Product audit 9.2.2.4 Product audit 4.4 Internal audit plans 9.2.2.1 Internal audit programme
4.1 Sample Bank Reconciliation Format . 4.2 Sample Cash Count and Verification . 4.3 Sample Internal Control Checklist . 4.4 Sample Reconciliation Problems and Tips . Section 6: Role of the Internal Audit . 6.1 Sample Internal Auditor Job Description . Section 7: Implementing the Internal Audit Function . 7.1 Sample Internal Audit Annual Work Plan
By CA Ravi Agarwal . Call/WHATSapp: 91-9330421952 91-8334866117 ViSit www.caraviagarwal.com TEST SERIES SYLLABUS FOR CA FINAL OLD . Audit 2 Audit of Banks 11 Audit of General Insurance Co 12 of Co-Op Society 13 Audit of NBFC 14 Audit Under Fiscal Laws 15 Cost Audit 16 02-03-202
CHAPTER 12 Internal Audit Charters and Building the Internal Audit Function 273 12.1 Establishing an Internal Audit Function 274 12.2 Audit Charter: Audit Committee and Management Authority 274 12.3 Building the Internal Audit Staff 275 (a) Role of the CAE 277 (b) Internal Audit Management Responsibilities 278 (c) Internal Audit Staff .
Internal Audit Boot Camp Session 2: Phases of an Audit Program . IA Boot Camp 03/17/21 National Indian Gaming Commission Page 17 of 26 . It is important to understand and include audit steps within your audit program. Audit steps can be updated and created during the planning phase. Audit steps provide the auditor with the proper guidance to
