1500 - 400 = how much sodium u can consume for the rest of the day
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
% = 2600/4000 = 0.65 = 65% fiction
Answer:
A) H0 : μ = 100
H1 : μ < 100
B) 39.2
C) We fail to reject null hypothesis
D) If the professor increases the sample size the value of the test statistic will increase .
Step-by-step explanation:
sample variance ( s ) = 80
sample size = 50
At ∝ = 0.01 population variance ( σ ) < 100
<u>a) Hypothesis </u>
H0 : μ = 100 ( Null hypothesis )
H1 : μ < 100 ( Alternate hypothesis )
<u>b) Determine The correct test statistic </u>
x^2 = ( n-1 ) * s^2/σ^2
= ( 49 ) * 80^2 / 100^2
= 39.2
<u>C) Determine the conclusion of the test</u>
The P-value = 0.1596 ( calculated )
The conclusion of the test is that we fail to reject null hypothesis given that
P-value ( 0.1596 ) > ∝ ( 0.01 )
D) If the professor increases the sample size the value of the test statistic will increase .
The numbers decreased from 2011 to 2012 from 410 units to 387 units. That's a descrease of 1,06%
