<span>P(B|A)=P(B)⋅P(A)
this is the answer</span>
Significant figures are the digits that carry meaning to its measurement. Significant figures includes all the numbers excluding all the leading zeros, trailing zeros. All non zero digits are significant. Zeros between the non zero digits are significant. In a decimal number, trailing zeros are significant.
Now, consider the given number 0.23350
Since, in a decimal number all the trailing zeros are significant.
So, in the number 0.23350 there are five significant figures 2,3,4,5 and 0.
Therefore, there are 5 significant figures in the given number.
Answer:
C.)9
Step-by-step explanation:
You add up all your data to get 54 and divide by the amount of numbers you had in the data which was 6. So if you divide 54 by 6 you get 9.
Hi!
We know the amount needed to make 8 pancakes. Dan wants to make 12 pancakes. 12/8 = 1,5, that's the ratio, we need to multiply each ingredient with 1.5 and we will get the amount needed to make 12 pancakes.
240 * 1,5 = 360 g of plain flour
2 * 1,5 = 3 eggs
600 * 1,5 = 900 ml of milk
Hope this helps!
Answer:
hello your question lacks the required options attached is a picture of the complete question
One would expect about 5% of tests to be significant just by chance if the null hypothesis is true, and for 60 tests, this is 0.05(60) = 3 tests. This could explain why these tests are statistically significant.
Step-by-step explanation:
What is misleading about this is the study's final report because this marketing study was carried out with a level of significance of 5% (0.05) which means that if we carry the same study with varying sample data we will mostly like arrive at a conclusion against our null conclusion 5% of the time and this is not good for the the study because it is a type 1 error and has to be eliminated and it cannot be eliminated totally .
hence One would expect about 5% of tests to be significant just by chance if the null hypothesis is true, and for 60 tests, this is 0.05(60) = 3 tests. This could explain why these tests are statistically significant.