What is 5 thousand 16 hundred 3 tens and 5 ones in standard form?

Suppose we are testing people to see if the rate of use of seat belts has changed from a previous value of 88%. Suppose that in

Andreas93 [3]

Answer:

a) We would expect to see 500*0.88=440

b) $z=\frac{0.9 -0.88}{\sqrt{\frac{0.88(1-0.88)}{500}}}=1.376$

$p_v =2*P(Z>1.376)=0.167$

So the p value obtained was a very high value and using the significance level assumed $\alpha=0.05$ we have $p_v>\alpha$ so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can said that at 5% of significance the true proportion is not significant different from 0.9.

The p value is a criterion to decide if we reject or not the null hypothesis, when $p_v$ we reject the null hypothesis in other case we FAIL to reject the null hypothesis. And represent the "probability of obtaining the observed results of a test, assuming that the null hypothesis is correct".

Step-by-step explanation:

Data given and notation

n=500 represent the random sample taken

X=450 represent the people that have the seat belt fastened

$\hat p=\frac{450}{500}=0.9$ estimated proportion of people that have the seat belt fastened

$p_o=0.88$ is the value that we want to test

$\alpha$ represent the significance level

z would represent the statistic (variable of interest)

$p_v{/tex} represent the p value (variable of interest) Part aWe would expect to see 500*0.88=440Part bConcepts and formulas to use We need to conduct a hypothesis in order to test the claim that the true proportion changes fro m 0.88.: Null hypothesis:[tex]p=0.88$

Alternative hypothesis: $p \neq 0.88$

When we conduct a proportion test we need to use the z statisitc, and the is given by:

$z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}}$ (1)

The One-Sample Proportion Test is used to assess whether a population proportion $\hat p$ is significantly different from a hypothesized value $p_o$ .

Calculate the statistic

Since we have all the info requires we can replace in formula (1) like this:

$z=\frac{0.9 -0.88}{\sqrt{\frac{0.88(1-0.88)}{500}}}=1.376$

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 assumed is $\alpha=0.05$ . The next step would be calculate the p value for this test.

Since is a bilateral test the p value would be:

$p_v =2*P(Z>1.376)=0.167$

So the p value obtained was a very high value and using the significance level assumed $\alpha=0.05$ we have $p_v>\alpha$ so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can said that at 5% of significance the true proportion is not significant different from 0.9.

The p value is a criterion to decide if we reject or not the null hypothesis, when $p_v$ we reject the null hypothesis in other case we FAIL to reject the null hypothesis. And represent the "probability of obtaining the observed results of a test, assuming that the null hypothesis is correct".

8 0

2 years ago

Saul tosses a coin 20 times and determines that the probability of turning heads is 0.55. Determine if this situation is theoret

strojnjashka [21]

Answer: Experimental Probability

Step-by-step explanation:

Theoretical Probability is the theory behind probability. Experimental (empirical) probability is probability calculated during experiments, direct observation, experience, or practice. The empirical probability, relative frequency, or experimental probability of an event is the ratio of the number of outcomes in which a specified event occurs to the total number of trials, not in a theoretical sample space but in an actual experiment.

7 0

2 years ago

Which equation has the correct sign on the product?

Alik [6]

Answer:

B

Step-by-step explanation:

(+)x(-)=(-)

(-)x(-)=(+)

8 0

2 years ago

In an experiment you do a chi-square test comparing observed and expected progeny. Your calculated chi square is 0.375. With 1 d

myrzilka [38]

Answer:

It mean that the observed progeny is similar than the expected progeny. There is no a relationship between the categorical variables.

Step-by-step explanation:

The Chi-squared test is used to test the relationship between categorical variables. A categorical variable is a non-numerical variable. The null hypothesis of the Chi-squared test is that categorical variables are independent; it means that the frequencies are not dependent on the variable. It is important to know that the Chi-squared test does not measure causality, it only measures the relationship. To reject the null hypothesis, you usually need a probability lower than 0.05, but in this case, the probability was way higher than 0.05, it was between 0.5 and 0.9.

4 0

3 years ago

Use the function g(x)-x+2 with initial values of 4, 2, and 1. What happens

kolezko [41]

Answer:

Step-by-step explanation:

The given function is , g(x)= - x + 2

For values of , is the sequence, -2,4,-2,4,-2,4........

For values of , is the sequence, 0,2,0,2........

For values of , is the sequence, 1,1,1,1,........

For initial value, of 4,the sequence converges to two values that is -2, 4.

For initial value of 2, the sequence again converges to two values which are 0,2.

For initial value of 1, the sequence converges to one value which is 1.

→→First Iterative value that is (-2)=Second iterative value (0) + 2 ×Third iterative value(1)

→→ First Iterative value that is (4)=Second iterative value (2) + 2 ×Third iterative value(1)

4 0

3 years ago