Answer:
0.008 meters
Step-by-step explanation:
Answer:
0.008 meters
Step-by-step explanation:
Hope this helps! :3
plz mark as brainliest!
Answer:
N → S (If national elections deteriorate into TV popularity contests, then smooth-talking morons will get elected.)
¬N → ¬S ( Therefore, if national elections do not deteriorate into TV popularity contests, then smooth-talking morons will not get elected.)
Step-by-step explanation:
¬ is a symbol of negation
→ is a symbol that represent "if... then..." scenario
Answer:
The answer is the first one.
Step-by-step explanation:
Okay, so the first one is solved like this:
You do 360*30%. 30% is 0.3 in decimal form. So 360*0.3=108. 108 is the amount that is discounted, NOT the price. You have to do 360-108, which is 252. The discounted price is $252.
Now the second one is solved like this:
You do 360*10% FIRST because the problem says it was marked 10% BEFORE the 20%. 10%=0.1, so 360*0.1=36. You subtract 360-36, which is 324. Then, you multiply 324 by 20% or 0.2, to get 64.8, which is the discount of 20%. You subtract 324-64.8, which is $259.20. So the first one is the answer because it is cheaper since 252 is less than 259.20. If you need this explanation, don't use this word for word. Summarize this in YOUR own words!
He should by the first washing machine because it cost less than the second washing machine.
The value of the unknown number is 11
Inequality is a concept in mathematics that shows the comparison between two non-equal numbers.
From the given information
∴
3x - 10 = 23
Collect like terms
3x = 23 + 10
3x = 33
Divide both sides by 3
x = 11
Learn more about inequality here:
Answer:
x = 11
Step-by-step explanation:
23 = 3x-10
1. Add 10 to both sides of the equation. -10 plus 10 is equal to zero so it cancels out to nothing, and 23 plus 10 is 33.
2. The new equation is now 33 = 3x.
3. Now you want to divide both sides by 3 to make x by itself since that is what you are trying to solve for.
4. 33/3 is equal to 11 so x = 11.
Answer:
No, the friend is not correct.
Step-by-step explanation:
The friend is not correct because let's call the three lines line A, line B, and line C. The line intersection says that if two lines intersect, then there will be one point of intersection. Therefore, we have to count all pairs of lines between line A, B, and C. Lines A and B can intersect, lines B and C can intersect, and lines A and C can intersect. Therefore there will be 3 lines of intersection, not 2.
half person).
Answer:
40.62
Step-by-step explanation:
that's the answer I got
a. If the sample variance is s^2=32 , are the data sufficient to conclude that the treatment has a significant effect using a two-tailed test with alpha=.05
b. If the sample variance is s^2=72 , are the data sufficient to conclude that the treatment has a significant effect using a two-tailed test with alpha=.05 ?
c. Comparing your answer for parts a and b, how does the variability of the scores in the sample influence the outcome of a hypothesis test?
A hypothesis test was conducted to evaluate the treatment's effect. For both variances, we failed to reject the null hypothesis, so we can't conclude that the treatment had a significant effect. The variability of scores plays a crucial role, as more variability makes it harder to identify a significant effect.
To determine if the treatment has a significant effect, we perform a hypothesis test using the sample mean (M), sample variance (s^2), and population mean (μ). The null hypothesis is that there's no effect from the treatment (μ=M), while the alternative hypothesis is that there is an effect (μ≠M).
a. For sample variance s^2=32, we can use the formula for the t score: t = (M - μ)/(s/√n) = (35 - 40)/(√32/√8) = -2.24. Based on a two-tailed t-distribution table, the critical t values for α=.05 and 7 degrees of freedom (n-1) are approximately -2.365 and 2.365. Our t value (-2.24) lies within this range, so we fail to reject the null hypothesis. We cannot conclude that the treatment has a significant effect.
b. Repeat the same process with sample variance s^2=72. The t value is now (35 - 40)/(√72/√8) = -1.48, again falling within the range of the critical t values. We can't conclude that the treatment has a significant effect.
c. As the variability (s^2) of the sample scores increases, it becomes more difficult to find a significant effect. Higher variability introduces more uncertainty, which can mask actual changes caused by the treatment.
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To evaluate the effect of a treatment using a two-tailed test with alpha = 0.05, we compare the calculated t-value to the critical t-value. The sample variance influences the outcome of the hypothesis test, with a larger variance leading to a wider critical region.
a. To test if the treatment has a significant effect, we will conduct a two-tailed hypothesis test using the t-distribution. The null hypothesis states that the treatment has no effect (μ = 40), while the alternative hypothesis states that the treatment has an effect (μ ≠ 40). With a sample size of 8, degrees of freedom (df) will be n-1 = 7. We will use the t-test formula to calculate the t-value, and compare it to the critical t-value from the t-table with α = 0.05/2 = 0.025. If the calculated t-value falls outside the critical region, we reject the null hypothesis and conclude that the treatment has a significant effect.
b. Similar to part a, we will conduct a two-tailed t-test using the same null and alternative hypotheses. With a sample size of 8, df = n-1 = 7. We will calculate the t-value using the sample mean, population mean, and sample variance. Comparing the calculated t-value to the critical t-value with α = 0.05/2 = 0.025, if the calculated t-value falls outside the critical region, we reject the null hypothesis and conclude that the treatment has a significant effect.
c. The variability of the scores in the sample, as indicated by the sample variance, influences the outcome of the hypothesis test. In both parts a and b, the sample variance is given. A larger sample variance (s^2 = 72 in part b) indicates more variability in the data, meaning the scores in the sample are more spread out. This leads to a larger t-value and a wider critical region. Therefore, it becomes easier to reject the null hypothesis and conclude that the treatment has a significant effect.
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