The answer would most likely be the first, second, and the third option.
Multiplication is a simple way of adding
For example 6x8 is the same as 8+8+8+8+8+8
Any number multiplied by 1 is itself E.g 4x1 = 4
Multiplying by 2 is just doubling
Multiplying by 10 is adding a 0 to the original number
If it is a big number that you do not know how to multiply mentally split it up
E.g 17x13
Split 13 into 10 and 3
17x10= 170
17x3= 51
Then add these numbers
221
If you ever get stuck, use the long method, add them instead, you will get to the right answer but it will take longer
Dividing is not as simple
Like multiplication dividing by one will leave you with the same answer
Dividing by two means you half the number, which may give you a decimal
Bigger numbers are trickier, and you may be allowed to use a calculator for numbers
Below are a number of links, these websites will teach you how to improve your multiplication and division skills:
http://www.bbc.co.uk/schools/gcsebitesize/maths/number/decimalsrev3.shtml
https://m.youtube.com/watch?v=XiXeu9FxAcQ
https://www.tutorialspoint.com/multiply_and_divide_whole_numbers/multiplication_as_repeated_addition.htm
The answer should be 282/77 as a fraction.
8,1/8 = 65/8
5,3/4 = 23/4
Multiply 65/8 by 23/4
= 1495/32
= 46 23/32 square feet (if they want it kept as a fraction)
Or 46.72 square feet (if they want a decimal)
Answer:
The correct option is c which is if this test was one-tailed instead of two-tailed, you would reject the null.
Step-by-step explanation:
a: This statement cannot be true as the p-value for a 1 tailed test is dependent on the level of significance and other features.
b: This statement cannot be true as there is no valid mathematical correlation between the p-value of the one-tailed test and the current p-value.
c: This statement is true because due to the enhanced level of significance, the null hypothesis will not be rejected.
d: This statement is inverse of statement c which cannot be true.
e: The statement cannot be true as there is no correlation between the current p-value and the p-value of 1 tailed test. The correlation exists between the values of one-tailed and two-tailed p-values.
