Unit 6 Day 5 Quiz Part B 4th Pd

4

A rapidly growing bacteria has been discovered. Its growth rate is shown in the chart.

Enter your data into L1 and L2.
Do an Exponential Regression to predict the number of bacteria after a number of hours.
Create the equation below.

Round the decimals to three places past the decimal point.
Use the math keyboard to create an exponent if needed.
Use 'bacteria' and 'hours' for variable names.
No spaces.

4

Using your equation for predicting the number of bacteria based on the number of hours that have passed, explain the rate of increase/decrease.

Use units and %.

Ex. The _____ decrease/increase by % per .

6

Predict the number of bacteria present after 8 hours.
1. Enter your prediction rounded to the nearest whole bacteria.
2. What kind of a prediction is this? Why?
3. Is this a wise or risky thing to do?

Answer all three questions for full credit.

6

Enter the data into L1 and L2 of your calculator.
Create a scatterplot to observe the relationship between time and soup temperature.
Describe it below:

4

Which regression seems to be the best model after looking ONLY at the scatterplot.

4

Do a linear regression, store the regression equation (StoreRegEq: VARS, Y-VARS, enter, enter, enter, enter)

Observe the residual plot, what do you see? (2nd, y=, change the ylist to RESID with 2nd, Stat)

4

Now check the exponential regression model, do an Exponential Regression (Stat, calc, 0)

Store the regression equation.

Observe the residual plot (see the previous question with instructions).
What do you see and what does this mean?

4

We are only considering the Linear Regression model or the Exponential Regression model.
Check the Coefficient of Determination (Rsquared) to decide which is the better model to use.

Redo the linear regression, this time noting the Rsquared value.

Select the Rsquared value for the linear regression:
LOOK CAREFULLY!

4

We are only considering the Linear Regression model or the Exponential Regression model.
Check the Coefficient of Determination (Rsquared) to decide which is the better model to use.

Redo the exponential regression, this time noting the Rsquared value.
Select the Rsquared value for the exponential regression:
LOOK CAREFULLY!

4

Based on your calculations and comparison of the Rsquared values, which regression is the better model?
Linear or Exponential?
Explain why for full credit.

4

Create the regression equation for making predictions of the soup temperature based on the elapsed time.
Linear Regression: stat, calc, 8
Exponential Regressin: stat, calc, 0

Use 'time' and temperature' for the variable names.
Indicate which variable is being predicted.
Round to three places past the decimal point.
No spaces.

4

Observe your regression equation carefully, explain the rate of decrease clearly.
Make sure to include units and the %.
Ex. use 'The ____ decreases/increases % per .'

4

Observe the residual plots shown below:
1. 2. 3. 4.
If each plot represents the residual plot from a regression equation, which plot(s) would cause you to reject the regression equation?
Why?

Select all answers.

0

BONUS
If a company being studied originally had $720,000 worth of sales and increased them by 14.5% each year , create an equation to predict their sales based on the years that had passed.

Use the correct notation to show what variable is being predicted.
Use the math keyboard to insert an exponent if needed.
No spaces.

0

BONUS:
If a person started out on America's Biggest Loser weighing 421 lb and lost at a rate of 5.2% each week, create a regression equation to predict their weight based on the number of weeks that had elapsed.

Use the correct notation to show what variable is being predicted.
Use the math keyboard to insert an exponent if needed.
No spaces.

Unit 6 Day 5 Quiz Part B 4th Pd

Using your equation for predicting the number of bacteria based on the number of hours that have passed, explain the rate of increase/decrease.Use units and %.Ex. The _____________________ decrease/increase by __________ % per ______________.

Predict the number of bacteria present after 8 hours.1. Enter your prediction rounded to the nearest whole bacteria.2. What kind of a prediction is this? Why?3. Is this a wise or risky thing to do?Answer all three questions for full credit.

Enter the data into L1 and L2 of your calculator.Create a scatterplot to observe the relationship between time and soup temperature.Describe it below:

Which regression seems to be the best model after looking ONLY at the scatterplot.

Do a linear regression, store the regression equation (StoreRegEq: VARS, Y-VARS, enter, enter, enter, enter)Observe the residual plot, what do you see? (2nd, y=, change the ylist to RESID with 2nd, Stat)

Now check the exponential regression model, do an Exponential Regression (Stat, calc, 0)Store the regression equation.Observe the residual plot (see the previous question with instructions).What do you see and what does this mean?

Based on your calculations and comparison of the Rsquared values, which regression is the better model?Linear or Exponential?Explain why for full credit.

Observe your regression equation carefully, explain the rate of decrease clearly.Make sure to include units and the %.Ex. use 'The __________________ decreases/increases ____________% per ______________.'

Observe the residual plots shown below: 1. 2. 3. 4. If each plot represents the residual plot from a regression equation, which plot(s) would cause you to reject the regression equation?Why?Select all answers.

Using your equation for predicting the number of bacteria based on the number of hours that have passed, explain the rate of increase/decrease.Use units and %.Ex. The _____________________ decrease/increase by __________ % per ______________.

Predict the number of bacteria present after 8 hours.1. Enter your prediction rounded to the nearest whole bacteria.2. What kind of a prediction is this? Why?3. Is this a wise or risky thing to do?Answer all three questions for full credit.

Enter the data into L1 and L2 of your calculator.Create a scatterplot to observe the relationship between time and soup temperature.Describe it below:

Which regression seems to be the best model after looking ONLY at the scatterplot.

Do a linear regression, store the regression equation (StoreRegEq: VARS, Y-VARS, enter, enter, enter, enter)Observe the residual plot, what do you see? (2nd, y=, change the ylist to RESID with 2nd, Stat)

Now check the exponential regression model, do an Exponential Regression (Stat, calc, 0)Store the regression equation.Observe the residual plot (see the previous question with instructions).What do you see and what does this mean?

Based on your calculations and comparison of the Rsquared values, which regression is the better model?Linear or Exponential?Explain why for full credit.

Observe your regression equation carefully, explain the rate of decrease clearly.Make sure to include units and the %.Ex. use 'The __________________ decreases/increases ____________% per ______________.'

Observe the residual plots shown below: 1. 2. 3. 4. If each plot represents the residual plot from a regression equation, which plot(s) would cause you to reject the regression equation?Why?Select all answers.

Using your equation for predicting the number of bacteria based on the number of hours that have passed, explain the rate of increase/decrease.

Use units and %.

Ex. The _____ decrease/increase by % per .

Predict the number of bacteria present after 8 hours.
1. Enter your prediction rounded to the nearest whole bacteria.
2. What kind of a prediction is this? Why?
3. Is this a wise or risky thing to do?

Answer all three questions for full credit.

Enter the data into L1 and L2 of your calculator.
Create a scatterplot to observe the relationship between time and soup temperature.
Describe it below:

Do a linear regression, store the regression equation (StoreRegEq: VARS, Y-VARS, enter, enter, enter, enter)

Observe the residual plot, what do you see? (2nd, y=, change the ylist to RESID with 2nd, Stat)

Now check the exponential regression model, do an Exponential Regression (Stat, calc, 0)

Store the regression equation.

Observe the residual plot (see the previous question with instructions).
What do you see and what does this mean?

Based on your calculations and comparison of the Rsquared values, which regression is the better model?
Linear or Exponential?
Explain why for full credit.

Observe your regression equation carefully, explain the rate of decrease clearly.
Make sure to include units and the %.
Ex. use 'The ____ decreases/increases % per .'

Observe the residual plots shown below:
1. 2. 3. 4.
If each plot represents the residual plot from a regression equation, which plot(s) would cause you to reject the regression equation?
Why?

Select all answers.

Using your equation for predicting the number of bacteria based on the number of hours that have passed, explain the rate of increase/decrease.

Use units and %.

Ex. The _____ decrease/increase by % per .

Predict the number of bacteria present after 8 hours.
1. Enter your prediction rounded to the nearest whole bacteria.
2. What kind of a prediction is this? Why?
3. Is this a wise or risky thing to do?

Answer all three questions for full credit.

Enter the data into L1 and L2 of your calculator.
Create a scatterplot to observe the relationship between time and soup temperature.
Describe it below:

Do a linear regression, store the regression equation (StoreRegEq: VARS, Y-VARS, enter, enter, enter, enter)

Observe the residual plot, what do you see? (2nd, y=, change the ylist to RESID with 2nd, Stat)

Now check the exponential regression model, do an Exponential Regression (Stat, calc, 0)

Store the regression equation.

Observe the residual plot (see the previous question with instructions).
What do you see and what does this mean?

Based on your calculations and comparison of the Rsquared values, which regression is the better model?
Linear or Exponential?
Explain why for full credit.

Observe your regression equation carefully, explain the rate of decrease clearly.
Make sure to include units and the %.
Ex. use 'The ____ decreases/increases % per .'

Observe the residual plots shown below:
1. 2. 3. 4.
If each plot represents the residual plot from a regression equation, which plot(s) would cause you to reject the regression equation?
Why?

Select all answers.