Explain why the data point, temperature 35 °C at 270 seconds, should not be used in the linear fit of the high temperature data.
Added by Timothy C.
Step 1
In this case, we are dealing with a set of temperature data collected over time, specifically focusing on high temperature readings. Show more…
Show all steps
Your feedback will help us improve your experience
Raymond Matshanda and 91 other Biology educators are ready to help you.
Ask a new question
Labs
Want to see this concept in action?
Explore this concept interactively to see how it behaves as you change inputs.
Key Concepts
Recommended Videos
A regression model is desired relating temperature and the proportion of impurity from a solid substance passing through solid helium. Temperature is listed in degrees centigrade. The data are as presented here (a) Fit a linear regression model. (b) Does it appear that the proportion of impurities passing through helium increases the temperature as it approaches -273 degrees centigrade? (c) Find $R^{2}$. (d) Based on the information above, does the linear model seem appropriate? What additional information would you need to better answer that question? $$ \begin{array}{cc} \text { Temperature } & \text { Proportion } \\ (\mathbf{C}) & \text { of Impurity } \\ \hline-260.5 & .425 \\ -255.7 & .224 \\ -264.6 & .453 \\ -265.0 & .475 \\ -270.0 & .705 \\ -272.0 & .860 \\ -272.5 & .935 \\ -272.6 & .961 \\ -272.8 & .979 \\ -272.9 & .990 \end{array} $$
Simple Linear Regression and Correlation
Test for Linearity of Regression: Data with Repeated Observations
Q5. The failure rate of certain electronic device is suspected to increase linearly with its temperature. Fit a least-squares linear line through the data in the following table. Table: The Failure Rate versus Temperature Temp: 55, 65, 75, 85, 95, 105, 55, 65, 75, 85, 95, 105 Failure Rate: 1.90, 1.93, 1.97, 2.00, 2.01, 2.01, 1.94, 1.95, 1.97, 2.02, 2.02, 2.04 a. Draw a scatter diagram. Comment on it. b. Estimate a simple linear regression equation and interpret the equation. c. Determine correlation coefficient and coefficient of determination and comment on them.
Supreeta N.
An experiment was conducted to observe the effect of an increase in temperature on the potency of an antibiotic. Three 1 -ounce portions of the antibiotic were stored for equal lengths of time at each of the following Fahrenheit temperatures: $30^{\circ}, 50^{\circ}, 70^{\circ},$ and $90^{\circ} .$ The potency readings observed at the end of the experimental period were as shown in the following table. $$\begin{array}{l|cccc}\text { Potency Readings }(y) & 38,43,29 & 32,26,33 & 19,27,23 & 14,19,21 \\ \hline \text { Temperature }(x) & 30^{\circ} & 50^{\circ} & 70^{\circ} & 90^{\circ}\end{array}$$ a. Find the least-squares line appropriate for this data. b. Plot the points and graph the line as a check on your calculations. c. Calculate $S^{2}$
Linear Models and Estimation by Least Squares
Properties of the Least-Squares Estimators: Simple Linear Regression
Recommended Textbooks
Biology for AP Courses
Objective Biology for NEET
Introduction to General, Organic and Biochemistry
Transcript
18,000,000+
Students on Numerade
Trusted by students at 8,000+ universities
Watch the video solution with this free unlock.
EMAIL
PASSWORD