Classify each polynomial according to its degree and type. Look at the screenshot below!
1 answer:
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The matrix is not properly formatted.
However, I'm able to rearrange the question as:
Operations:
Please note that the above may not reflect the original question. However, you should be able to implement my steps in your question.
Answer:
Step-by-step explanation:
The first operation:
This means that the new second row (R2) is derived by:
Multiplying the first row (R1) by 2; add this to the second row
The row 1 elements are:
Multiply by 2
Add to row 2 elements are:
The second operation:
This means that the new third row (R3) is derived by:
Multiplying the first row (R1) by -3; add this to the third row
The row 1 elements are:
Multiply by -3
Add to row 2 elements are:
Hence, the new matrix is:
Answer:
The null and alternative hypothesis can be written as:
Step-by-step explanation:
This is a hypothesis test for the difference between proportions.
The claim is that the proportion of 18- to 34-year-old Americans that own a cell phone is less than the proportion of 35- to 49-year-old Americans.
This claim will be reflected in the alternnative hypothesis, that will state that the population proportion 1 (18 to 34) is significantly smaller than the population proportion 2 (35 to 49).
On the contrary, the null hypothesis will state that the population proportion 1 is ot significantly smaller than the population proportion 2.
Then, the null and alternative hypothesis can be written as:
The significance level is assumed to be 0.05.
The sample 1, of size n1=200 has a proportion of p1=0.63.
The sample 2, of size n2=175 has a proportion of p2=0.68.
The difference between proportions is (p1-p2)=-0.05.
The pooled proportion, needed to calculate the standard error, is:
The estimated standard error of the difference between means is computed using the formula:
Then, we can calculate the z-statistic as:
This test is a left-tailed test, so the P-value for this test is calculated as (using a z-table):
As the P-value (0.1554) is bigger than the significance level (0.05), the effect is not significant.
The null hypothesis failed to be rejected.
There is not enough evidence to support the claim that the proportion of 18- to 34-year-old Americans that own a cell phone is less than the proportion of 35- to 49-year-old Americans.