Syllabus

Statistics Honors

Week 1: Welcome to Statistics Honors
Essential Question: How do we get started?
Objectives:
• Familiarize yourself with the rules and policies of the course
• Get comfortable navigating D2L
• Understand what is expected of you throughout the course
• Get to know your classmates by creating a blog
• Examine a statistical study and participate in a discussion

Week 2: Introduction to Data
Essential Question: How can we organize information?
Objectives:
• Identify basic statistical terms
• Distinguish the difference between categorical (qualitative) data and quantitative data
• Distinguish the difference between a population and a sample
• Identify procedures in data collection
• Identify and classify different sampling techniques
• Identify errors in data collection
• Analyze collected data

Week 3: Summarizing Categorical Data
Essential Question: How can we interpret categorical data?
Objectives:
• Identify one-way and two-way tables
• Interpret contingency tables
• Identify, create and analyze visual displays of categorical data
• Compare and contrast data displayed in a table and in a graph
• Interpret categorical data to draw conclusions

Week 4: Summarizing Quantitative Data
Essential Question: How can we analyze quantitative data?
Objectives:
• Identify, compare and find measures of central tendency
• Identify, compare and find measures of variability
• Identify the center, spread, shape and unusual features of a data set
• Analyze quantitative data to draw conclusions

Week 5: Graphs of Quantitative Data
Essential Question: How can we display quantitative data?
Objectives:
• Identify patterns of data
• Identify distribution shapes
• Identify components of a histogram
• Interpret and analyze histograms to draw conclusions

Week 6: More Graphs of Quantitative Data
Essential Question: How can we display quantitative data?
Objectives:
• Identify dotplots, stemplots, and boxplots
• Create the different types of quantitative displays
• Interpret and analyze quantitative data using various graphs and displays
• Compare and contrast different graphs of quantitative data

Week 7: Data Analysis
Essential Question: How can we compare data distributions?
Objectives:
• Use numerical representations to describe data
• Use graphical representations to describe data
• Compare data distributions in terms of shape, center and spread
• Participate in a group project analyzing data

Week 8: Measuring Position
Essential Question: How can we interpret the position of data?
Objectives:
• Identify, find and compare percentiles
• Relate quartiles and percentiles
• Interpret the position of data values
• Identify and interpret z-scores

Week 9: The Normal Distribution
Essential Question: What is normal?
Objectives:
• Identify the standard normal distribution
• Draw a normal curve labeling z-scores and shade area under the curve
• Identify the different types of area under the curve
• Find the areas under the normal curve

Week 10: Bivariate Data and Scatter Plots
Essential Question: How can we determine if there is a relationship between two variables?
Objectives:
• Define bivariate data and scatter plots
• Identify and interpret scatter plot trends in terms of strength, direction, and unusual features
• Graph scatter plots
• Distinguish the difference between association and correlation

Week 11: Linear Regression
Essential Question: How can we model the linear relationship between two quantitative variables?
Objectives:
• Determine if a scatter plot shows a linear relationship
• Define a least-squares regression line
• Identify the slope and y-intercept of a linear data set
• Identify the regression line that models the linear relationship between two quantitative variables
• Make predictions using the regression line
• Distinguish the difference between extrapolation and interpolation

Week 12: Bivariate Data Analysis
Essential Question: What conclusions can we draw from bivariate data?
Objectives:
• Use numerical representations to describe bivariate data
• Use graphical representations to describe bivariate data
• Compare bivariate data in terms of direction, form, strength and unusual features
• Participate in a group project analyzing bivariate data

Week 13: Combinatorics and Probability
Essential Question: Is what should happen what will happen?
Objectives:
• Identify the Counting Principle
• Find the sample space of an experiment
• Identify and find permutations
• Identify and find combinations
• Find the probability of simple events
• Distinguish the difference between theoretical and experimental probability

Week 14: Probability Rules!
Essential Question: How can we find the probability of more than one event occurring?
Objectives:
• Identify compound events
• Identify and find the complement of an event
• Identify mutually exclusive events and non-mutually exclusive events
• Find the probability of mutually exclusive events
• Identify independent and dependent events
• Find the probability of independent and dependent events

Week 15: Summing Up Statistics
Essential Question: What did you learn in this course?
Objectives:
• Complete final course assessment
• Participate in a final discussion about careers in statistics
• Create a statistics scrapbook
• Complete a reflection journal
• Create a farewell graduation speech
• Complete the course survey and the VHS student survey