Rita ran 5 miles in 48 minutes what was her time per mile

Simplify 8 - (-5) - 4(-7). -63 -15 41 68

jekas [21]

The correct answer is 41.

3 0

2 years ago

The average daily high temperature in °C) in Karachi, Pakistan, on the tth day of the year is

kvasek [131]

Answer:

The highest would be 34 degrees Celsius and the lowest would be 24 degrees Celsius.

Step-by-step explanation:

What I did was make a graph. The 29 in the beginning of the function represents the vertical shift, meaning the "midline" would be y = 29. The -5 after the 29 represents the amplitude. From there, you can go 5 under 29 (24 degrees Celsius) and 5 over 29 (34 degrees Celsius).

3 0

2 years ago

Which expression is equivalent to b^-3/ab^-3?

Mrrafil [7]

1/a

The b^-3 in the denominator and numerator cancel out

7 0

2 years ago

Use the diagram of the parallelogram to find the length of side PL and the measure of angle R.

Oxana [17]

The explanation is in a file the other Pearson put

4 0

2 years ago

Read 2 more answers

Gibbs Baby Food Company wishes to compare the weight gain of infants using its brand versus its competitor’s. A sample of 40 bab

Leviafan [203]

Answer:

$z=\frac{(7.6-8.1)-0}{\sqrt{\frac{2.3^2}{40}+\frac{2.9^2}{55}}}}=-0.936$

The p value can be founded with this formula:

$p_v =P(z$

Since the p value is higher than the significance level provided of 0.05 we have enough evidence to FAIL to reject the null hypothesis and we can't conclude that the true mean for the Gibbs brand is significantly lower than the true mean for the competitor

Step-by-step explanation:

Information given

$\bar X_{1}=7.6$ represent the mean for Gibbs products

$\bar X_{2}=8.1$ represent the mean for the competitor

$\sigma_{1}=2.3$ represent the population standard deviation for Gibbs

$\sigma_{2}=2.9$ represent the sample standard deviation for the competitor

$n_{1}=40$ sample size for the group Gibbs

$n_{2}=55$ sample size for the group competitor

$\alpha=0.05$ Significance level provided

z would represent the statistic

Hypothesis to verify

We want to check if babies using the Gibbs brand gained less weight, the system of hypothesis would be:

Null hypothesis: $\mu_{1}-\mu_{2}=0$

Alternative hypothesis: $\mu_{1} - \mu_{2}< 0$

The statistic would be given by:

$z=\frac{(\bar X_{1}-\bar X_{2})-\Delta}{\sqrt{\frac{\sigma^2_{1}}{n_{1}}+\frac{\sigma^2_{2}}{n_{2}}}}$ (1)

Replacing the info given we got:

$z=\frac{(7.6-8.1)-0}{\sqrt{\frac{2.3^2}{40}+\frac{2.9^2}{55}}}}=-0.936$

The p value can be founded with this formula:

$p_v =P(z$

Since the p value is higher than the significance level provided of 0.05 we have enough evidence to FAIL to reject the null hypothesis and we can't conclude that the true mean for the Gibbs brand is significantly lower than the true mean for the competitor

5 0

2 years ago