DS 250 - Intro to Data Analysis for Bus

March 3, 2023

Project2.docx

o your scatterplot as outlined in part b;

o your answers for parts c through f;

c). correlation coefficient = -0.814

d). predict for 2.0 liters

In this case, the equation is: City Mileage = -8.4667(Engine Size) + 44.84, so City Mileage = -8.4667(2.0) +

44.84 = 27.91.

e). slope

Slope (b) = r * (Sy / Sx) = -0.814 * (5.241 / 0.581) = -7.367

f). quantitative independent variables. The gradient can be used

X-intercept 4.526825127

Y-intercept 47.09016393

o your calculations and results for part g (optional).

=CORREL (B2:B11,C2:C11)

Second, we can calculate the correlation coefficient (r) using the following formula:

r = Σ[(xi - x̄)(yi - ȳ)] / √[Σ(xi - x̄)² * Σ(yi - ȳ)²]

Where Σ is the sum of all values, xi and yi are the individual values of the independent and dependent variables,

respectively.

Let's substitute the values:

r = [(1.2-2.0)(36-27.3) + (1.5-2.0)(31-27.3) + (1.6-2.0)(32-27.3) + (1.6-2.0)(31-27.3) + (2.0-2.0)(25-27.3) +

(2.0-2.0)(28-27.3) + (2.3-2.0)(22-27.3) + (2.4-2.0)(23-27.3) + (2.5-2.0)(23-27.3) + (2.7-2.0)(21-27.3)] / √[(1.2-

2.0)²+(1.5-2.0)²+(1.6-2.0)²+(1.6-2.0)²+(2.0-2.0)²+(2.0-2.0)²+(2.3-2.0)²+(2.4-2.0)²+(2.5-2.0)²+(2.7-2.0)²] * √[10-

1]

r = -0.814