# regression

1. ### Predicted Probability

Someone created a spreadsheet to graph predicted provability values on a Logistic Regression S Graph. There are four values used. a = Assumed Maximum b = Assumed Minimum c = Raw Data St. Dev (Field Data) d = Model Output (Research Data) the formula used if the following NORMSDIST...
2. ### Gravity model

Hi I am currently writing an assignment regarding a trade model using a gravity equation. The dependent variable in the model is Ln(X) and the non-dependent is both Ln (GDP, distance and so on) AND binary variables. So the question is: can I use SPSS for this kind of modelling or would...
3. ### Introductory references about total least squares

I am an engineering student and I've been recently told about the Total Least Square (TLS) method. I am interested in applying it to topographic measurements and in comparing the results with the ordinary least squares (OLS) solution. I've been searching a lot but I couldn't find any tutorial...
4. ### Regression: DV is Revenue and IDV is cost. (Very High MAPE)

Need help on one of the modelling assignment. My dependent variable is Revenue and the independent variable is Cost beside some other variables like Temperature etc. My concern is about how shall i improve the MAPE given that the revenue does not behave in a particular pattern with regards...
5. ### Std. Error Multiple Regression Question

Hi guys, I'm stuck at interpreting the stadard error. In single regression it's clear, it's just the average distance from the line. But I don't really understand what this looks like in multiple regression. Does the standart error depend on the estimate or do I have to look at it in an...
6. ### How to measure the impact of a subject on student performance?

Hi, I need to find the impact of mathematics on student performance. I have only the student exam marks for mathematics and all the other subjects. What are the statistical methods that can be used for this situation other than correlation and regression? According to my point of view, I...
7. ### Cox regression with varying data completion

Gentlemen Many thanks for providing a fantastic resource in many previous projects, I have often found very helpful answers to simple questions browsing the forums here. Today however I have become unstuck. Please forgive my poor basic understanding of stats. My usual statistician has been...
8. ### Prediction Intervals

I am in the process of calculating the prediction intervals on a time series data linear regression model The independent variable in my model is time measured as 1,2,3,4,...,40. I have a dependent variable which is a continuous variable. Now when calculating the prediction intervals using...
9. ### Split file regression, or Fixed effects Mixed model

Within a dataset that has a few variables explaining dependent variable A, and influences vary over different categories, it can be obvious to split the file in these categories and run a regression. However, there is also the possibility of running mixed models with fixed factors. What would...
10. ### CI for Dependent Variable in Multiple Linear Regression

I have a regression model but I want to get a 95% confidence interval of the dependent variable for given values of the independent variables. I found that for a single factor regression: Confindence interval = t(alpha, DofF) * SYX * SQRT(1/n+(X-XAVG)^2/SSX) where n is the number of...
11. ### Reporting results of nonparametric regression

Hi! I am wondering how you present the results of non parametric regression test. I run the nonparametric regression using R, and the package np I get p- values but no df or t statistic. For example For the normal regression tests I did with other data, I presented the sample size, degrees...
12. ### nested fixed effects possible?

Hi, I investigate a problem via a regression model. Firtsly, I have two different ways to measure my outcome, which I incorporate as a two-level factor variable X. However, each of these methods is again influenced by a factor variable with two levels, but these factor variables differ for...
13. ### New Linear Regression Approach - Link Here

My company has just released a free software download that eliminates known issues associated with traditional techniques. The InoraRAE has a simple interface and calculates fast, accurate results, making it more meaningful and useful than any linear regression tool before it. It is available...
14. ### Regression on Survey analysis across 50 states

I ran a survey across all 50 states in the US. The goal is to see if there is a correlation between people's love for the state and the population growth % over 5 years. The survey has 15 questions - all on Likert scale (1 to 5 Strongly Disgaree to Strongly Agree) - questions about people's...
15. ### Conceptual queries in modeling

Hi all, I am from engineering background. I would require your help in certain conceptual questions in modeling. Your help would be greatly appreciated! Following are my few questions... (Pointers on these questions would help me , else you may direct me to any useful resources.) 1)If a...
16. ### Violating Homogeneity

Hi, if in regression models homogeneity is violated, the variance can in principle depend on both: Predictor and outcome variable(s). In case of a dependency on categorical or continuous predictor variables, there are many ways to model different dependencies, e.g. using GLS models. In...
17. ### Problem log(0) practical solution?

Hello everyone, I want to model the association of a score (range 0-125) and age with an exponential approach because my scatterplot show an exponential progression. My approach is: I do log(score) -> do a linear regression with age as covariate -> do exp(regression coefficients)...
18. ### [SAS] Compare predicted vs actual continuous [0,1] data

Hello, I have predicted values for year and quarter that were calculated from a linear regression, and I also have actual values. I would like to compare the actual vs. predicted values to ensure that the model was appropriate. The data are continuous on [0,1]. I had tried a chi-squared...
19. ### Questions in implementing Considering Canonical Correlation Analysis in R

I have a dataset of temperature readings of different burner parts which determine the final temperature of the burner and time to set off burner So my dataset looks like this: Knob_reading_of_Coil_temperature(P1) Knob_reading_of_barrel_temperature(P2)...
20. ### Hypothesis:

If you wanted your null hypothesis to be that y and x are linearly related, and your alternative to be that they are quadratic. What could you use as your null and alternative hypothesis, and how would you go about testing it?