What the App Does

• Predicts a car’s miles per gallon (MPG) using cylinders, horsepower, and weight.
• Lets users adjust inputs and see instant results.
• Visualizes your prediction with a highlighted point on the MPG plot.

How it Works

• User selects cylinders, horsepower, and weight.
• The server runs a linear regression model in real-time.
• Output: predicted MPG and a visual comparison in the dataset.

## Warning: package 'ggplot2' was built under R version 4.4.3

Technical Details

• Model: Linear regression (mpg ~ cyl + hp + wt).
• Dataset: Classic mtcars (R datasets).
• Platform: Shiny for interactivity.
• Red point marks user-selected prediction.

Try It Yourself

• App link: [https://raunaksingh.shinyapps.io/devloping_data_prod/]
• Source code: [https://github.com/RonnyBoy16/developing-data-prods-final]
• To use: Choose values, view instant MPG prediction.

## 
## Call:
## lm(formula = mpg ~ cyl + hp + wt, data = mtcars)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -3.9290 -1.5598 -0.5311  1.1850  5.8986 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 38.75179    1.78686  21.687  < 2e-16 ***
## cyl         -0.94162    0.55092  -1.709 0.098480 .  
## hp          -0.01804    0.01188  -1.519 0.140015    
## wt          -3.16697    0.74058  -4.276 0.000199 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2.512 on 28 degrees of freedom
## Multiple R-squared:  0.8431, Adjusted R-squared:  0.8263 
## F-statistic: 50.17 on 3 and 28 DF,  p-value: 2.184e-11