BACHELOR OF BUSINESS ADMINISTRATION

Detailed explanation-1: -In statistics, a spurious correlation (or spuriousness) refers to a connection between two variables that appears to be causal but is not. With spurious correlation, any observed dependencies between variables are merely due to chance or are both related to some unseen confounder.

Detailed explanation-2: -The assumptions are as follows: level of measurement, related pairs, absence of outliers, and linearity. Level of measurement refers to each variable. For a Pearson correlation, each variable should be continuous.

Detailed explanation-3: -A zero correlation exists when there is no relationship between two variables. For example there is no relationship between the amount of tea drunk and level of intelligence.

Detailed explanation-4: -If the correlation coefficient has a negative value (below 0) it indicates a negative relationship between the variables. This means that the variables move in opposite directions (ie when one increases the other decreases, or when one decreases the other increases).

Detailed explanation-5: -A correlation between variables indicates that as one variable changes in value, the other variable tends to change in a specific direction. Understanding that relationship is useful because we can use the value of one variable to predict the value of the other variable.