It is based on the other measure we have plotted. Looking at the past trend can help us predict future values of a measure.Minimum and maximum values, and identify clusters. Used when you want to look at the exact data points in your data.Suitable to identify a linear or non-linear relationship in the data.Use when you want to find out the correlation between two numerical variables/measures.Some customers want cheaper cell phones even if they donвЂ™t have great performance. Customers prefer getting lower-price but good-performance cell phones, while fewer customers are looking for high-end and high-priced cell phones. Cluster 1 in blue color has more outliers as compared with cluster 3. (low price, high rating) in orange color is most dense and tightly packed. A few outliers are indicating larger area houses available for lower prices.ДЇigure 6 shows three different color-coded clusters giving us an immediate idea that cluster 2.It is like logarithmic, power, polynomial, etc. We can try different trend line models provided by Tableau.It has a p-value less than 0.0001 and R-squared 0.33, indicating that this might not be the best model. We have drawn a linear trend line in which both variables that transforms by the natural logarithm ln(Y), ln(X) before the model is estimate.Here, we can see from Figure 2 that data points are concentrate in the lower price and lower area range.So, We will plot a scatter plot of two measures вЂ“ area against price and the trend lines for both. As a general rule, a low p-value usually less than 0.005 and an R-squared value closer to 1 signifies a good model.ДЇor instance, let us look at a use case with a data set containing different dimensions like furnishing вЂ“ furnished or unfurnished, locality, status вЂ“ ready to move or almost ready, transaction вЂ“ New or resale, type вЂ“ apartment or builder floor (entire floor for the occupant), per square feet price and price. They give us the p-value and R-squared values, which tell us how well our line is fitting to the data. They indicate how strong or weak the relationship is and if any outliers are affecting the trend line.

Such that it is the best fit for the data. A trend line is an equation that shows the relationship between measures. The line passing through the points is naming a trend line which shows the correlation of variables. Negative: As x co-ordinate increases, y co-ordinate decreases.

A scatter plot