Quantitative Methods and Analysis
Predicting the probability of achieving the desired results often involves the comparison of two groups. For example, politicians would like to know who is more likely to vote for them, and they will compare the data of potential voters: younger and older, males and females, urban and rural, and so on. Similarly, employees would like to know whether their salary depends more on experience or level of education. Hence, hypothesis testing with two samples may be of great value. In addition, statisticians often make better predictions if they know whether one variable is related to the other. That is, when comparing two variables and attempting to see whether there is a relationship between them, analysts will try to determine whether changes made to one variable trigger corresponding changes in the other variable.
1. Describe the purpose of scatter diagrams, and discuss how you would determine whether positive, negative, or no correlation exists between two variables by looking at the scatter diagram.
Sample Solution
Quantitative methods and analysis
Quantitative methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaire, and surveys, or by manipulating pre-existing statistical data using computational techniques. A scatter diagram is a type of diagram or mathematical diagram using Cartesian coordinates to display values for typically two variables for a set of data. If the points are coded, one additional variable can be displayed. A scatter diagram can show a positive relationship, a negative relationship, or no relationship. If the points on the scatter diagram seem to form a line that slants up from left to right, there is a positive correlation between the variables. Scatter diagrams usually consist of a large body of data. If the line goes from a high value on the y-axis down to a high-value on the x-axis, the variables have a negative correlation.
