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

• Complete a survey telling me about yourself and your school

• 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