Introductory Statistics Q3
Section outline
-
-
Introductory Statistics
Learning Objectives: I can distinguish between univariate and bivariate data. I can identify the independent and dependent variables in a data set. I can construct and interpret scatter plots in terms of direction, form and strength.
-
-
-
-
-
-
Students mustReceive a grade
-
-
-
Correlation & Regression
Learning Objectives: I can use Google Sheets to create a scatter plot. I can calculate and interpret the correlation coefficient for a data set. I understand the difference between correlation and causation. I can use Google Sheets to calculate a regression equation. I can interpret and use the regression equation to calculate predicted values.
-
-
-
-
-
-
-
-
-
-
-
Correlation vs Causation Project
Learning Objectives: I can identify the different types of logical fallacies that can be made when incorrectly citing causation. I can use the correlation coefficient to determine the strength of a correlation between variables. I can use the regression equation to predict future events.
-
-
-
Students mustReceive a grade
-
-
-
-
-
-
Linear & Nonlinear Regressions
Learning Objectives: I can determine when a nonlinear regression fits the data best. I can use Google Spreadsheets to create a scatterplot, a nonlinear trendline and find the regression equation. I can use the regression equation to predict future values.
-
-
-
-
-
Students mustReceive a grade
-
-
-
-
-
-
Data Analyzation & Decision Making
Learning Objectives: I can analyze and interpret data to inform decisions. I understand that using numerical data and experiential data is the best way to make decisions.
Mrs. Scholes is out of town Monday - Thursday this week. Please contact Mrs. Annie Swinton if you need help or have questions about your assignments this week.
Your assignments in Week 5 will be graded by Mrs. Scholes when she returns on Friday. If you would like to make revisions to your submitted assignments after Friday, I will leave your assignments open for you past the deadline with no penalty.
-
-
-
Students mustReceive a grade
-
-
-
Students mustReceive a grade
-
-
-
-
Outliers & Extrapolation
Learning Objectives: I can identify outliers in scatter plots and I understand their effect on the correlation coefficient and regression line. I know the difference between extrapolation and interpolation. I can predict unknown values and determine the appropriateness of the predictions. I can calculate residuals and create a residual plot. I know how to analyze a residual plot to determine the reasonableness of my predictions.
-
-
-
-
Students mustReceive a grade
-
-
-
-
-
The United States of Obesity Project
Learning Objectives: I can synthesize what I know about bivariate data, correlation, outliers, regression and extrapolation and use it to answer real world problems. I can write the null and alternate hypotheses for claims in hypothesis testing.
-
-
-
-
-
Students mustReceive a grade
-
-
-
-
-
Hypothesis Testing
Learning Objectives: I understand the difference between Type 1 and Type 2 errors in hypothesis testing. I know how to interpret these types of errors in the context of a problem. I understand the purpose of using the standard normal distribution in hypothesis testing. I can use the z-table to find z-critical values. Using z-critical values, I can calculate critical values and conclude if we should reject or fail to reject the null hypothesis.
-
-
-
-
-
-
-
-
-
-
Students mustViewReceive a grade
-
-
-
Hypothesis Testing
Learning Objectives: I can answer a hypothesis test question using the information and steps I've learned the past two weeks. I can make correct conclusions and interpret the results.
All work is due on Thursday, March 15th by 6pm.
-
-
Students mustMark as done
Week 9: Lessons & Assignments
-
-
Students mustReceive a grade
-