Let's break down the problem based on the image.

We are given data about Biaya Pemasaran (Marketing Cost) and Volume Penjualan (Sales Volume) over the years from 2012 to 2018. The tasks are:

1. Regression Equation (Persamaan Regresi): This refers to finding the linear regression equation $y = a + bx$, where $y$ is the dependent variable (Volume Penjualan) and $x$ is the independent variable (Biaya Pemasaran).
2. Correlation Coefficient (r): Calculate the correlation coefficient $r$, which measures the strength and direction of the linear relationship between the two variables.
3. Contribution of Variables (Kd and Knd): Calculate the coefficient of determination $R^2$ (which tells us how much variance in $y$ is explained by $x$) and the remaining variance that is unexplained ( $1 - R^2$).
4. t-statistic (t-hitung): Calculate the t-value to test if the regression coefficient $b$ is significantly different from zero.

I'll start by computing the linear regression equation and the correlation coefficient. Let's denote:

• $X$: Biaya Pemasaran
• $Y$: Volume Penjualan

The data is as follows:

• $X = \{3, 4, 2, 3, 5, 4, 5\}$ (Biaya Pemasaran)
• $Y = \{47, 52, 23, 58, 62, 42, 67\}$ (Volume Penjualan)

Let me calculate the regression equation and the correlation coefficient for you.It seems like I can't do more advanced data analysis right now. Please try again later.

If you'd like, I can guide you through solving it manually:

1. Use the least squares method to calculate the regression equation $y = a + bx$.
2. Find the correlation coefficient $r$ using the formula for Pearson's $r$.
3. The coefficient of determination $R^2$ is $r^2$.
4. For $t$-statistic, use $t = \frac{b}{SE_b}$, where $SE_b$ is the standard error of the slope.

Would you like assistance on any of these steps?

Here are 5 related questions:

1. How do you calculate the correlation coefficient $r$ manually?
2. What are the steps involved in calculating the slope and intercept for linear regression?
3. What does the $R^2$ value tell us about the relationship between variables?
4. How can you interpret the $t$-statistic result for significance testing?
5. What does a higher $r$-value mean in the context of correlation?

Tip: When calculating $R^2$, remember it's simply the square of the correlation coefficient $r$.