An athlete runs 5 miles in 25 minutes and then changes their pace to run the next 3 miles in 15 minutes. Overall, what is the average time in minutes it takes the athlete to run 1 mile?

Before we compare the values of the options, we convert the decimals to fractions.

5.4 becomes 54/10

6.25 becomes 625/100

Thus, the set of fractions is 11/2, 54/10, 13/3, 625/100. The least common denominator for 2, 10, 3, and 100 is 300, which we use to compare each options given.

11/2*300=1650

54/10*300=1620

13/3*300=1300

625/100*300=1875

From the above, 1875 is the greatest value which corresponds to 6.25. Therefore, 6.25 is the greatest value of all the choices given.

We asked to convert kg to pounds. There are two ways of converting between kg and pounds

And

Since we are to find pounds, we use the second option for kg to cancel

The pound equivalent of 45 kg is 99 lb.

From the given estimations, we can find the exact sum after adding the given numbers and see the trend the student utilizes to find their estimates. The actual sum is as follows

26+180=206

115+391=506

497+2024=2521

From the above evaluation, the students round the exact sum to the nearest tens. So, in the problem we need to approximate 545+7501.

545+7501=8046

The exact sum is 8046 and the approximate value after rounding to the nearest tens is 8050.

The babies' measured weights change over time and depend on the time interval after birth. Since weight is the outcome being measured, it is the dependent variable in the study.

 we are to find the selling price of the sweater from the marked price and the discount. The marked price is given as

Discount=mark off rate*original price

Discount=15%*$78

Convert 15% into a fraction, which become 15/100=0.15. Then

Discount=0.15*$78=$11.70

The selling price of the sweater will be the original price less the discount or mark off value. Then,

Thus, the approximate selling price of the sweater is $66.

correlations fall into positive, negative, and no correlation. A positive correlation shows that an increase in one variable increase results in an increase on the other variable increases as shown.

A negative correlation scatter plot shows that an increase in one variable results in a decrease on the other one.

The no-correlation scatter plot demonstrates that there is no response between variables. A change in one variable has no effect on the other variable.

Looking at the provided scatter plot, the heights of the students does not have any relationship on the students’ scores. Thus, the type of correlation is no correlation.

Correlation of two variables falls into:

Positive correlation: an increase in one variable causes another variable to increase

Negative correlation: an increase in one variable causes another one to decrease

No correlation: a change in one variable does not cause any response in another variable.

From the given choices

Option a is no correlation

Option b is a negative correlation

Option c is a negative correlation

Option d is a positive correlation

Thus, the correct statement is a.

Let's calculate the number of each color of gumball:

• Red: 20% of 120 → 0.2×120=24
• Orange: 30% of 120 → 0.3×120=36
• Yellow: 5% of 120 → 0.05×120=6
• Green: 10% of 120 → 0.1×120=12
• Blue: The remaining percentage: 100%−(20%+30%+5%+10%) = 100%−65% =35%
• So, 0.35×120=42 blue gumballs.

Now, we find how many more blue gumballs there are than yellow:

42−6=36

In this problem, we need to find the amount of gratuity the couple will leave. The gratuity is 16% of the total bill. Before solving the problem, the following are terms and their meaning in percent problems:

• Is means equals
• Of means multiply
• What means unknown (variable)

If we let x be the amount of gratuity, then translating the given problem into a mathematical equation becomes:

So, the value of x=9.376 and to the nearest cent, x=9.38

There, a couple will leave a gratuity of $9.38.

The distribution of the weights of the newborn babies is symmetric meaning the mean, mode, and median are all equal. Thus, the bell-shape curve describes this kind of distribution of weights