there are 4 tens in a deck so probability of picking a ten is 4/52 reduced to 1/13
there are 13 clubs in a deck, probability for that is 13/52 reduced to 1/4
probability for both is 1/13 x 1/4 = 1/52
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
I think it is BD but I’m not 100% sure
Answer:
its the first one
Step-by-step explanation:
I used a calc
It is a little difficult to see the graph but I am assuming that the x-axis is temperature in Celsius and the y-axis is temperature in Fahrenheit.
Since the y-intercept is always the point at which the x-value is equal to 0, in this case the y-intercept would be the Fahrenheit temperature that is equivalent to 0°C.
I hope this helps.
