Multiple Linear
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What is a Multiple Linear Regression?
Multiple linear regression is a statistical technique in which we have one dependent and several independent variables. Suppose the problem we are looking at can be treated as a problem of one dependent and several independent variables. In that case, it is suitable to use the multiple regression method for data analysis.
Where is linear regression usually used?
An Example Of Multiple Regression Analysis
For example, a researcher wants to examine whether stress level and anxiety level predict test scores. In that case, we have one dependent variable – the exam result, and two independent variables – stress level and anxiety level.
What are the use of null and alternative hypothesis for the Simple Linear Regression?
Therefore, we test the following hypotheses:
Null hypothesis: The stress level and anxiety level do not significantly predict exam scores.
Alternative hypothesis: The stress level and anxiety level significantly predict exam scores.
R function to Compute Multiple Linear Regression
The code to run a Linear Regression using R is as follows:
lm (DV~ IV1 +IV2,+…+IVx data = dataframe)
DV: dependent variable
IV: Independent variables
In this section, we will show you how to run the multiple linear regression using the r studio program and how to interpret the test results after we obtain the result of the test. In the first part, we present the r program code and function for the linear regression analysis. Next, you will see the outputs as a result of running the r codes. In the last section, you can find the interpretation of the multiple linear regression in APA format.
# LOAD DATA
library(readxl)
Data <- read_excel(“Data.xlsx“)
# VIEW DATA
View(Data)
# NAME VARIABLES
data <- Data
stress <- data$stress
anxiety <- data$anxiety
exams <- data$exams
# PERFORM MULTIPLE LINEAR REGRESSION
reg <- lm(exams ~ anxiety + stress, data = data)
summary(regression)
> reg <- lm(exams ~ anxiety + stress, data = data)
> summary(regression)##
## Call:
## lm(formula = exams ~ stress, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -31.50 -15.87 -8.88 22.82 34.76
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 67.2573 4.6028 14.612 <2e-16 ***
## stress -0.3769 0.7793 -0.484 0.63
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 21.55 on 97 degrees of freedom
## Multiple R-squared: 0.002406, Adjusted R-squared: -0.007879
## F-statistic: 0.2339 on 1 and 97 DF, p-value: 0.6297Reporting Multiple Linear Regression in R
Multiple regression was conducted to determine whether stress level and anxiety level predict exam scores. The equation for the regression line is
exam score = 60.72 + 1.26*anxiety level – 0.47*stress level
R-squared = 0.03, indicating that just 3% of the variance in exam scores is explained by stress level and anxiety level. The results of ANOVA were non-significant, F(2, 96) = 1.41, p = 0.249. We, therefore, fail to reject the null hypothesis that the slope of our regression line is zero and conclude that stress level and anxiety level do not significantly predict exam scores. Anxiety level is non-significant positive predictor of exam score (b = 1.26, p = 0.111). Stress level is non-significant negative predictor of exam score (B = -0.47, p = 0.546)
GET HELP FROM US
There is a lot of statistical software out there, but R is one of the most popular. If you’re a student who needs help with R Studio, there are a few different resources you can turn to. We prepared a page for R tutorial for Beginners. All contents can guide you through Step-by-step R data analysis tutorials and you can see Basic Statistical Analysis Using the R Statistical Package.
The second option is that you can get help from us, we give R Studio help for students with their assignments, dissertation, or research. Doing it yourself is always cheaper, but it can also be a lot more time-consuming. If you’re not the best at SPSS, then this might not be a good idea. It can take days just to figure out how to do some of the easier things in SPSS. So paying someone to do your R task will save you a ton of time and make your life a lot easier.
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