Question: Tell whether each function is linear or non-linear.
1 answer:
Just to avoid some confusion: <u>the first picture is a graph of function A, and the second picture is a graph of function B. </u>
Answer:
D. Function A is non-linear and Function B is linear.
Step-by-step explanation:
A good way to find out if a function is linear is by graphing it. If you graph it and it is a straight line, then it is linear.
So, let's graph the given points from the table of Function A and see if it forms a straight line. When you connect the dots, it's not straight, so Function A is non-linear.
Now let's look at function B. We can graph that too with the given information from the equation - the slope is -1 and the y-intercept is 5. (If you are a bit confused on how to graph it, don't hesitate to ask!) It does form a straight line, so Function B is linear.
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Answer:
So the p value obtained was a very low value and using the significance level given we have
so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 5% of significance the proportion of interest is significantly higher than 0.5.
Step-by-step explanation:
Data given and notation
n=502 represent the random sample taken
X=331 represent the adults that said they would not be bothered if the NAtional security agency
estimated proportion of people who would not be bothered if the NAtional security agency
is the value that we want to test
represent the significance level
Confidence=99% or 0.99
z would represent the statistic (variable of interest)
represent the p value (variable of interest)
Concepts and formulas to use
We need to conduct a hypothesis in order to test the claim that the true proportion is higher than the majority of 0.5:
Null hypothesis:
Alternative hypothesis:
When we conduct a proportion test we need to use the z statistic, and the is given by:
(1)
The One-Sample Proportion Test is used to assess whether a population proportion is significantly different from a hypothesized value
.
Calculate the statistic
Since we have all the info requires we can replace in formula (1) like this:
Statistical decision
It's important to refresh the p value method or p value approach . "This method is about determining "likely" or "unlikely" by determining the probability assuming the null hypothesis were true of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed". Or in other words is just a method to have an statistical decision to fail to reject or reject the null hypothesis.
The significance level provided . The next step would be calculate the p value for this test.
Since is a right tailed test the p value would be:
So the p value obtained was a very low value and using the significance level given we have
so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 5% of significance the proportion of interest is significantly higher than 0.5.