when is the appropriate to model data with a linear function. give example of a real world data that can modeled with a linear f
1 answer:
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Answer:
$29500
Step-by-step explanation:
We have been given that Tariq lives in Palm Beach, Florida, and purchased a house for $250,000. The amount of millage for property tax is 11.8%. We are asked to find the amount of property tax that Tariq paid.
To find the amount of property tax paid by Tariq, we need to calculate 11.8% of $250,000.
Therefore, Tariq paid an amount of $29500 in tax.
Answer:
Reject <em>H</em>₀. There is a significant difference in drug resistance between the two states.
Step-by-step explanation:
In this case we need to determine whether the data suggest a statistically significant difference between the proportions of drug-resistant cases in the two states.
The significance level of the test is, <em>α</em> = 0.02.
(1)
The hypothesis can be defined as follows:
<em>H</em>₀: There is no difference between the proportions of drug-resistant cases in the two states, i.e. .
<em>Hₐ</em>: There is a statistically significant difference between the proportions of drug-resistant cases in the two states, i.e. .
(2)
Compute the sample proportions and total proportion as follows:
Compute the test statistic value as follows:
The test statistic value is 2.86.
(3)
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:
<em>p</em>-value = 0.00424 < <em>α</em> = 0.02.
The null hypothesis will be rejected at 0.02 significance level.
Reject <em>H</em>₀. There is a significant difference in drug resistance between the two states.