It depends on the method one uses, but the Pearson correlation coefficient is the most widely used. Values in the form of numbers show the direction and how strong the relationship is between two different variables. These can range from -1.00 up to +1.00. If it is positive it is a direct relationship. For example, if one increases the other will also increase. The opposite is also true, if one value goes down. the other will too. If it is negative, it is an inverse response that is recorded. In one example, say that one value increases, the other decreases. Here as well, the opposite is true if one decreases …show more content…
It is of great importance because it is a good way to predict future performance when we look to past performance in certain areas. One example that is helpful to understand is electricity use. If it is hot, electricity usage rises as people use more power for cooling buildings. This is a positive correlation. In the winter months, some may use less electricity. Instead of using electricity to power heating devices, some may use oil or natural gas to heat, therefore the use of electricity will fall. This is a negative correlation. A correlation at zero is unpredictable, and use of electricity in the spring or fall may be just that. During these seasons, different regions and different people may experience different temperatures. Some may turn their heating systems on earlier than others, while others may keep their cooling systems on longer than others. This is up to personal taste and is unpredictable and …show more content…
The alternative hypothesis is the existing hypothesis that has already been proven or maintained as the true outcome. For instance, water is wet. This is the alternative hypothesis, which is also known as the maintained hypothesis. If a researcher would like to explore different possibilities, a new study will be conducted with a new hypothesis which would be quickly disproven. Of course water is wet, and any other hypothesis would be the null