## Programming Logic

Steps to fit the linear regression model for relationship between dependent and independent variables.

**Step 1:**

Find the correlation between dependent variable cpi and independent variables year and quarter

**Step 2:**

Scatter plot dependent vs independent variables

**Step 3:
**Fit the linear regression model and determine the coefficients

**Step 3:**

Using the model predict the cpi for each quarter of year 2015

**Step 4:**

Plot the cpi for previous years and for the predicted year

## Plot to visualize the correlation

# cpi~ year + quarter

# plot cpi vs quarter to see the relationship

# plot cpi for each quarter for three years

# define x axis manually using axis function

plot(cpi, xaxt="n", ylab="CPI", xlab="")

axis(1, labels=paste(year, quarter, sep="-Q"), at=1:12, las=3)

## Predict using linear regression model

# predict cpi for each quarter of year 2015

data2015 = data.frame(year=2015, quarter=1:4)

cpi2015 = predict(lrm, newdata = data2015)

cpi2015

# 1 2 3 4

# 174.7083 175.9417 177.1750 178.4083