Linear regression where am i going wrong?

In summary, linear regression is a statistical method that models the relationship between a dependent variable and one or more independent variables, assuming a linear relationship between the variables. To determine if your data is suitable for linear regression, you must meet certain assumptions, such as a linear relationship, equal variance, and normally distributed errors. There are two types of linear regression: simple and multiple, which differ in the number of independent variables used. The results of a linear regression include an equation, R-squared value, and coefficients, which can be used to make predictions and understand the impact of the independent variables on the dependent variable. If the model does not fit the data well, it may be due to assumptions violations or outliers, and adjustments can be made to
  • #1
Scarpetta
4
0
linear regression where am i going wrong??

Linear regression using least square fit method for the
determination of cocaine sample
Cocaine (mg/ml) Peak height
X= 2.75 Y=27377 X squared=0.9625 X x Y=3241.272

M = 10 x 3241.272 – 2.75 x 27377 / 10 x 0.9625 – 7.5625

= -42874.03 / 2.0625 = -20787.39 ?

I should be getting m = 267.25 according to graph
Can anyone tell me where I am going wrong please:yuck:
 
Last edited:
Physics news on Phys.org
  • #2
Hey! Is helping you on this problem going to get us in trouble with the DEA?

Carl
 

1. What is linear regression?

Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables. It assumes that there is a linear relationship between the variables, meaning that as one variable changes, the other variable changes in a consistent and predictable manner.

2. How do I know if my data is suitable for linear regression?

There are a few assumptions that need to be met in order for linear regression to be an appropriate model for your data. These include a linear relationship between the variables, homoscedasticity (equal variance), and normally distributed errors. You can check these assumptions by visually inspecting your data and conducting statistical tests.

3. What is the difference between simple and multiple linear regression?

Simple linear regression involves only one independent variable, while multiple linear regression involves two or more independent variables. In simple linear regression, the relationship between the dependent variable and independent variable is represented by a straight line. In multiple linear regression, the relationship is represented by a plane or hyperplane, depending on the number of independent variables.

4. How do I interpret the results of a linear regression?

The results of a linear regression will typically include the equation for the line or plane of best fit, the coefficient of determination (R-squared), and the coefficients for each independent variable. The equation can be used to make predictions about the dependent variable based on the values of the independent variable(s). The R-squared value indicates the proportion of variability in the dependent variable that can be explained by the independent variable(s). The coefficients represent the amount of change in the dependent variable for every unit change in the independent variable(s).

5. What should I do if my model does not fit the data well?

If your model does not fit the data well, it may be due to violations of the assumptions of linear regression or the presence of outliers. You can try transforming the data, removing outliers, or considering a different model. It is also important to carefully consider the variables included in the model and their potential impact on the dependent variable. You may also need to gather more data or refine your research question in order to better understand the relationship between the variables.

Similar threads

  • Set Theory, Logic, Probability, Statistics
Replies
6
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
8
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
3
Views
700
  • Engineering and Comp Sci Homework Help
Replies
7
Views
686
  • Set Theory, Logic, Probability, Statistics
Replies
30
Views
2K
  • Set Theory, Logic, Probability, Statistics
Replies
23
Views
2K
  • Set Theory, Logic, Probability, Statistics
Replies
4
Views
1K
  • Calculus and Beyond Homework Help
Replies
3
Views
2K
  • Set Theory, Logic, Probability, Statistics
Replies
1
Views
1K
  • Introductory Physics Homework Help
Replies
10
Views
974
Back
Top