Answer: The answer is (C) Exponential.
Step-by-step explanation: We are to select out of the given options the type of graph that a savings account with compounded interest be modelled.
We know that compounding gives more interest because we are earning interest on interest, and not just on the principal.
The formula foe compound interest is given by
where, 'P' is the principal, r is the rate of interest and 'n' is the number of years.
Therefore, we can see that the function is of exponential type.
If we draw the graph of compound interest earned every year with a particular rate of interest is of exponential type.
So, the correct option is (C) Exponential.
A.27 hours
B.15 hours
C.6 hours
D.3.1 hours
Answer:
The volume of the original chamber is 102.02cubic inches. This is 242.47 cubic inches less than the volume of the new chamber.
Hope this helps! I got it right on the Plato/Edmentum mastery test ♡
Answer:
Step-by-step explanation:
The equation of ellipse is given as:
(1)
Now, from the given information, The ellipse passes through (0, 58), (0, -58), (21, 29), thus equation (1) becomes:
⇒
⇒
Also,
⇒
⇒
⇒
⇒
Now, substituting the values of in the equation (1), we have
which is the required equation for ellipse.
Answer:
what is math
Step-by-step explanation:
I want to teach you how to use a plane mirror to see if I want to go would have clear photo pathaununa is the best person like cmt thorai vyo
yeah a successful and non uniform and non-uniform is used for free a plane mirror a convex lens for Canon printer and non-uniform a successful and rich
y=x+5
Answer:
false
Step-by-step explanation:
no solution
I did it on a graph and I think its true?
Answer:
Less than 4% of a company's widgets are defective.
Step-by-step explanation:
In this case we want to be reasonably certain that less than 4% of a company's widgets are defective.
The significance level of the test is, α = 0.01.
The hypothesis can be defined as follows:
H₀: At least 4% of a company's widgets are defective, i.e. p ≥ 0.04.
Hₐ: Less than 4% of a company's widgets are defective, i.e. p < 0.04.
The information provided is:
n = 250
x = 6
The sample proportion is,
Compute the test statistic value as follows:
The test statistic value is -1.29.
The decision rule is:
The null hypothesis will be rejected if the p-value of the test is less than the significance level.
Compute the p-value as follows:
So,
p-value = 0.0985 > α = 0.01.
The null hypothesis will not be rejected at 1% significance level.
Thus, there is not enough evidence to support the claim.
Conclusion:
Less than 4% of a company's widgets are defective.
This is a hypothesis testing problem where we test the claim that less than 4% of widgets are defective. We set the null and alternative hypotheses, confirm conditions for a binomial distribution, compute the test statistic, find the p-value and then make a conclusion based on the comparison of p-value with the given significance level.
In this scenario, we are interested in testing the hypothesis about the proportion of defective widgets. We define our null hypothesis (H0) and the alternative hypothesis (Ha) as follows:
H0: p = 0.04 (The proportion of defective widgets is 4%)
Ha: p < 0.04 (The proportion of defective widgets is less than 4%)
The conditions for a binomial distribution are met here, as each widget is either defective or not, and each widget is tested independently. Also, the quantities np and nq (where n is the sample size and q is the probability of failure) are greater than five, so we can approximate by the normal distribution.
We calculate the test statistic using the formula: z = (p' - p) / sqrt [ (p * q) / n ]
Where, p' is the sample proportion, which is 6/250, p is the hypothesized proportion which is 0.04, q is 1 - p and n is the sample size (250). This gives us a z value. Then, we find the p-value from the standard normal distribution using this z value. If p-value < α (0.01), we reject the null hypothesis. Otherwise, we do not reject it.
At the end, you will conclude. If we reject the null, we say, 'At the 1 percent significance level, there is sufficient evidence to conclude that less than 4% of the company's widgets are defective'. If we don't reject the null, 'At the 1 percent significance level, there is insufficient evidence to conclude that less than 4% of the company's widgets are defective.'
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