Author: Marianna Bonanome (Page 13 of 14)

Learning Outcomes.

• Collect, organize and graph raw data.
• Compute statistical parameters (covariance, correlation coefficient).
• Compute a regression equation and use it to make predictions.

Topic. This lesson covers: Least Squares Method and Regression

• Openstax Introductory Statistics:
  • 12.4 Testing the Significance of the Correlation Coefficient
  • 12.5 Prediction
• Introductory Statistics by Sheldon Ross, 3rd edition: Sections 12.1-12.3
• Statistics with Microsoft Excel by Beverly J. Dretzke, 5th ed., SLOPE, INTERCEPT P. 205 – 210

 WeBWorK Sets: Continue working on Sets 12.2 & 12.3 – 2/23 at 5 pm.

Learning Outcomes.

• Collect, organize and graph raw data.
• Compute statistical parameters (covariance, correlation coefficient).
• Compute a regression equation and use it to make predictions.

Topic. This lesson covers: Covariance and Coefficient of Correlation

• Openstax Introductory Statistics:
  • 12.2 Scatter Plots
  • 12.3 The Regression Equation
• Introductory Statistics by Sheldon Ross, 3rd edition: Sections 2.5, 3.7
• Statistics with Microsoft Excel by Beverly J. Dretzke, 5th ed., COV(X,Y), CORREL(X,Y)

WeBWorK. Sets 12.2 and 12.3 opens 8 am 2/10, due 5 pm 2/23

Learning Outcomes.

• Compute statistical parameters (mean, median, mode, average deviation, variance, and sample standard deviation)

Topic. This lesson covers: Measures of Central Location and Variability

• Openstax Introductory Statistics:
  • 2.3 Measures of the Location of the Data
  • 2.5 Measures of the Center of the Data
  • 2.6 Skewness and the Mean, Median, and Mode
  • 2.7 Measures of the Spread of the Data
• Introductory Statistics by Sheldon Ross, 3rd edition: Sections 3.2-3.5
• Statistics with Microsoft Excel by Beverly J. Dretzke, 5th ed., AVERAGE( : ), VARP( : ), STDEVP( : ), P. 36 – 45

WeBWorK. Sets 2.5, 2.6 & 2.7 opens 2/9, 8 am due 2/16, 8 am