![\left[\begin{array}{ccc}2&6&3\\-5&1&4\end{array}\right]](https://tex.z-dn.net/?f=%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D2%266%263%5C%5C-5%261%264%5Cend%7Barray%7D%5Cright%5D)
R1 ÷ 2 = ![\left[\begin{array}{ccc}1&3&1.5\\-5&1&4\end{array}\right]](https://tex.z-dn.net/?f=%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D1%263%261.5%5C%5C-5%261%264%5Cend%7Barray%7D%5Cright%5D)
R2 ÷ -5 = ![\left[\begin{array}{ccc}1&3&1.5\\1&-0.2&-0.8\end{array}\right]](https://tex.z-dn.net/?f=%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D1%263%261.5%5C%5C1%26-0.2%26-0.8%5Cend%7Barray%7D%5Cright%5D)
R2: R1 - R2 = ![\left[\begin{array}{ccc}1&3&1.5\\0&3.2&2.3\end{array}\right]](https://tex.z-dn.net/?f=%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D1%263%261.5%5C%5C0%263.2%262.3%5Cend%7Barray%7D%5Cright%5D)
R2 ÷ 3.2 = ![\left[\begin{array}{ccc}1&3&1.5\\0&1&0.71875\end{array}\right]](https://tex.z-dn.net/?f=%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D1%263%261.5%5C%5C0%261%260.71875%5Cend%7Barray%7D%5Cright%5D)
R1: R1 - 3R2 = ![\left[\begin{array}{ccc}1&0&0.65625\\0&1&0.71875\end{array}\right]](https://tex.z-dn.net/?f=%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D1%260%260.65625%5C%5C0%261%260.71875%5Cend%7Barray%7D%5Cright%5D)
Answer: x = 0.65625, y = 0.71875
Answer:
well i know you have that done now
Step-by-step explanation:
Answer:
C. with 3000 successes of 5000 cases sample
Step-by-step explanation:
Given that we need to test if the proportion of success is greater than 0.5.
From the given options, we can see that they all have the same proportion which equals to;
Proportion p = 30/50 = 600/1000 = 0.6
p = 0.6
But we can notice that the number of samples in each case is different.
Test statistic z score can be calculated with the formula below;
z = (p^−po)/√{po(1−po)/n}
Where,
z= Test statistics
n = Sample size
po = Null hypothesized value
p^ = Observed proportion
Since all other variables are the same for all the cases except sample size, from the formula for the test statistics we can see that the higher the value of sample size (n) the higher the test statistics (z) and the highest z gives the strongest evidence for the alternative hypothesis. So the option with the highest sample size gives the strongest evidence for the alternative hypothesis.
Therefore, option C with sample size 5000 and proportion 0.6 has the highest sample size. Hence, option C gives the strongest evidence for the alternative hypothesis
Answer:
1.2
Step-by-step explanation:
Since we are rounding it by the tenth, it means we are rounding to the 1st digit to the right of the decimal.
We know 7 is greater then 5 meaning we round up
.1 + .1 is equal to .2 meaning its 1.2
If you still don't understand, I recommend you talk to your teacher
