Answer:2
8
2
+
2
8
Step-by-step explanation:
Answer:
84x
Step-by-step explanation:
If you have any questions feel free to ask in the comments.
Answer:
about 20
Step-by-step explanation:
The vehicle must decline in value by $25,635 -10,000 = $15,635. At the rate of $3000 per year, it will take ...
15,635/3,000 ≈ 5.21167
In 5.2 years, she will be about 20 years old.
Answer:
Step-by-step explanation:
Solution:-
State the hypotheses. The first step is to state the null hypothesis and an alternative hypothesis.
Null hypothesis: The distribution of severity of psoriasis cases at the end and prior are same.
Alternative hypothesis: The distribution of severity of psoriasis cases at the end and prior are different.
Formulate an analysis plan. For this analysis, the significance level is 0.05. Using sample data, we will conduct a chi-square goodness of fit test of the null hypothesis.
Analyze sample data. Applying the chi-square goodness of fit test to sample data, we compute the degrees of freedom, the expected frequency counts, and the chi-square test statistic. Based on the chi-square statistic and the degrees of freedom, we determine the P-value.
DF = k - 1 = 4 - 1
D.F = 3
(Ei) = n * pi
Category observed Num expected num [(Or,c -Er,c)²/Er,c]
Remission 380 20 6480
Mild
symptoms 520 770 81.16883117
Moderate
symptoms 95 160 24.40625
Severe
symptom 5 50 40.5
Sum 1000 1000 6628.075081
Χ2 = Σ [ (Oi - Ei)2 / Ei ]
Χ2 = 6628.08
Χ2Critical = 7.81
where DF is the degrees of freedom, k is the number of levels of the categorical variable, n is the number of observations in the sample, Ei is the expected frequency count for level i, Oi is the observed frequency count for level i, and Χ2 is the chi-square test statistic.
The P-value is the probability that a chi-square statistic having 3 degrees of freedom is more extreme than 6628.08.
We use the Chi-Square Distribution Calculator to find P(Χ2 > 19.58) =less than 0.000001
Interpret results. Since the P-value (almost 0) is less than the significance level (0.05), we cannot accept the null hypothesis.
We reject H0, because 6628.08 is greater than 7.81. We have statistically significant evidence at alpha equals to 0.05 level to show that distribution of severity of psoriasis cases at the end of the clinical trial for the sample is different from the distribution of the severity of psoriasis cases prior to the administration of the drug suggesting the drug is effective.
The chi-square test is a statistical method that determines if there's a significant difference between observed and expected frequencies in different categories, such as symptom status in this clinical trial. Without post-treatment numbers, we can't run the exact test. However, if the test statistic exceeded the critical value, we could conclude that the drug significantly affected symptom statuses.
This question pertains to the use of a chi-squared test, which is a statistical method used to determine if there's a significant difference between observed frequencies and expected frequencies in one or more categories. For this case, the categories are the symptom statuses (remission, mild, moderate, and severe).
To conduct a chi-square test, you first need to know the observed frequencies (the initial percentages given in the question) and the expected frequencies (the percentages after treatment). As the question doesn't provide the numbers after treatment, I can't perform the exact chi-square test.
If the post-treatment numbers were provided, you would compare them to the pre-treatment numbers using the chi-squared formula, which involves summing the squared difference between observed and expected frequencies, divided by expected frequency, for all categories. The result is a chi-square test statistic, which you would then compare to a critical value associated with a chosen significance level (commonly 0.05) to determine if the treatment has a statistically significant effect.
To interpret a chi-square test statistic, if the calculated test statistic is larger than the critical value, it suggests that the drug made a significant difference in the distribution of symptom statuses. If not, we can't conclude the drug was effective.
#SPJ3
B) The graph is discrete because there cannot be negative values for altitude.
C) The graph is continuous because there can be fractional values for time.
D) The graph is continuous because there can be negative values for altitude.
Answer:
Option c
Step-by-step explanation:
Given that a hot air balloon descends to the ground.
The function
can be used to describe the altitude of the balloon as it approaches the ground.
Here t = time and h = height
Since t cannot be negative we can t starting from 0
t can take any fractional value and h is well defined for any value of t positive
So option c is right
Step-by-step explanation:
(2x-y+3)(2x-y-3)=
4x²-2xy-6x-2xy+y²+3y+6x-3y-9=
4x²-4xy+y²-9=
(2x-y)²-9
The number of cupcakes needed to get the order to 100% is 6 cupcakes.
The percentage is calculated by dividing the required value by the total value and multiplying by 100.
Example:
Required percentage value = a
total value = b
Percentage = a/b x 100
Example:
50% = 50/100 = 1/2
25% = 25/100 = 1/4
20% = 20/100 = 1/5
10% = 10/100 = 1/10
We have,
60% = 9 cupcakes
Multiply 100/60 on both sides.
100/60 x 60% = 100/60 x 9 cupcakes.
100% = 5 x 3 cupcakes
100% = 15 cupcakes
Thus,
6 morecupcakes are needed.
Learn more about percentages here:
#SPJ2
Answer:
6 more cupcakes.
Step-by-step explanation:
60% of 15 is 9, so 15-9 is 6.
Answer:
48
Step-by-step explanation:
3.2 - 3 = .2
3(.2) = .6
9 + .6 = 9.6
5 * 9.6 = 48