Answer:
54
Step-by-step explanation:
Angles in a triangle add to 180° and we can see a right angle so
x = 180 - ( 90 + 36 )
x = 180 - 126
x = 54
Answer:
26 meters
Step-by-step explanation: Ez. First add all the data you already have. You should end up with 19. Then, you want to find the length of the missing side. Well, we know it's 7 meters since its opposite is 7, and these lengths are in the same square. So 19+7 is 26 meters.
Answer:
D. If the P-value is large, reject the null hypothesis of no interaction. Conclude that there is an interaction effect.
Step-by-step explanation:
If p value is smaller than significant level(5% or 1%), then reject the null hypothesis.
From the given information about two way ANOVA, First 3 are true statements based on decision rule.
4th statement is false, becasue p value is larger, then decision is to fail the null hypothesis and conclude that there is no interaction between them
There could be a strong correlation between the proximity of the holiday season and the number of people who buy in the shopping centers.
It is known that when there are vacations people tend to frequent shopping centers more often than when they are busy with work or school.
Therefore, the proximity in the holiday season is related to the increase in the number of people who buy in the shopping centers.
This means that there is a strong correlation between both variables, since when one increases the other also does. This type of correlation is called positive. When, on the contrary, the increase of one variable causes the decrease of another variable, it is said that there is a negative correlation.
There are several coefficients that measure the degree of correlation (strong or weak), adapted to the nature of the data. The best known is the 'r' coefficient of Pearson correlation
A correlation is strong when the change in a variable x produces a significant change in a variable 'y'. In this case, the correlation coefficient r approaches | 1 |.
When the correlation between two variables is weak, the change of one causes a very slight and difficult to perceive change in the other variable. In this case, the correlation coefficient approaches zero
