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lozanna [386]
3 years ago
12

Fernando is 6 feet tall.if 1 inch is approximately 2.54 cm,what is fernandos height in cm.

Mathematics
2 answers:
otez555 [7]3 years ago
8 0

Answer:

182.88cm

Step-by-step explanation:

i looked it up

neonofarm [45]3 years ago
6 0

Answer:

Step-by-step explanation:

Maybe try to multiply or divide.

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A jet travels from chicago to kansas city at a speed of 440 knots. If it takes a plane 3 hr longer to fly from kansas city to ch
steposvetlana [31]

d = distance between the two cities

v₁ = average speed while going from chicago to kansas city = 440 knots

t₁ = time taken to travel distance going from chicago to kansas city

time taken to travel distance going from chicago to kansas city is given as

t₁ = d/v₁

t₁ = d/440                                        eq-1


v₂ = average speed while going from kansas city to chicago = 110 knots

t₂ = time taken to travel distance going from kansas city to chicago

time taken to travel distance going from kansas city to chicago is given as

t₂ = d/v₂

t₂ = d/110                                                     eq-2


Given that :

t₂ = t₁ + 3

using eq-1  and eq-2

(d/110) = (d/440) + 3

d = 440

7 0
3 years ago
The sine of angle θ is 0.3.<br><br> What is cos(θ)?
Sergio [31]

The answer:

\sqrt{9}1 /10

Explanation to your question:

Since the sin of theta is 0.3, we can reasonably deduct that the opposite side to theta has a ration of 3 to 10 to that of the hypotenuse. Thus, the adjacent side to theta, using the pythagorean theorem, will be root91. Therefore, since the cosine of theta is the adjacent/hypotenuse, we get root 91/10

6 0
2 years ago
Help me please and thank you ​
goldenfox [79]
I believe the answer is 78.54 , D
4 0
3 years ago
Read 2 more answers
The null hypothesis for an ANOVA is that all treatments/samples come from populations with the same mean. The alternative hypoth
Charra [1.4K]

Answer:

At least one of the population means is different from the others.

Step-by-step explanation:

ANOVA is a short term or an acronym for analysis of variance which was developed by the notable statistician Ronald Fisher. The analysis of variance (ANOVA) is typically a collection of statistical models with their respective estimation procedures used for the analysis of the difference between the group of means found in a sample. Simply stated, ANOVA helps to ensure we have a balanced data by splitting the observed variability of a data set into random and systematic factors.

In Statistics, the random factors doesn't have any significant impact on the data set but the systematic factors does have an influence.

Basically, the analysis of variance (ANOVA) procedure is typically used as a statistical tool to determine whether or not the mean of two or more populations are equal through the use of null hypothesis or a F-test.

Hence, the null hypothesis for an ANOVA is that all treatments or samples come from populations with the same mean. The alternative hypothesis is best stated as at least one of the population means is different from the others.

5 0
3 years ago
In the July 2007 issue, Consumer Reports examined the calorie content of two kinds of hot dogs: meat (usually a mixture of pork,
kifflom [539]

Answer:

Since we FAIL to reject the null hypothesis, then if we construct an interval of 95% of confidence, the 0 should be included, because on the test hypothesis we conclude that there would be no significant difference between the means of the two groups analyzed, and the results obtained on the hypothesis test needs to be consistent with the confidence interval.

Step-by-step explanation:

A hypothesis is defined as "a speculation or theory based on insufficient evidence that lends itself to further testing and experimentation. With further testing, a hypothesis can usually be proven true or false".  

The null hypothesis is defined as "a hypothesis that says there is no statistical significance between the two variables in the hypothesis. It is the hypothesis that the researcher is trying to disprove".

The alternative hypothesis is "just the inverse, or opposite, of the null hypothesis. It is the hypothesis that researcher is trying to prove".

\bar x_{meat}=111.7 represent the sample mean of calories for the meat hot dogs

\bar x_{beef}=135.4 represent the sample mean of calories for the beef hot dogs

The system of hypothesis on this case would be:

Null hypothesis: \mu_{meat}-\mu_{beef}=0

Alternative hypothesis: \mu_{meat}-\mu_{beef}\neq 0

On this case we have the p value obtained, after calculate the statistic and we got that p_v =0.124 if we select a 5% significance level \alpha=0.05 we see that p_v >\alpha and on this case we can FAIL to rejec the null hypothesis, so there is not a significant difference between the mean of the two tpes of hot dogs analyzed at 5% of significance.

And since we FAIL to reject the null hypothesis, then if we construct an interval of 95% of confidence, the 0 should be included, because on the test hypothesis we conclude that there would be no significant difference between the means of the two groups analyzed, and the results obtained on the hypothesis test needs to be consistent with the confidence interval.

8 0
3 years ago
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