Statistics, help please!?
The amounts of electric bills for all households in a city have a probability distribution with a mean of $80 and a standard deviation of $25. Find the probability that the mean amount of electric bills for a random sample of 75 households selected from this city will be (a) between $72 and $77 (b) within $6 of the population mean (c) more than the population mean by at least $5 (d) determine the 97th percentile of the distribution of X
Statistics help please?
ANSWER: Coca-Cola is equally preferred and not preferred over other brands. Why??? POPULATION PROPORTION HYPOTHESIS TESTING, NORMAL DISTRIBUTION 7-Step Procedure 1. PARAMETER OF INTEREST: p = POPULATION PROPORTION 2. HYPOTHESES : NULL HYPOTHESIS H0: p = 0.50 (50% perfer Coca-Cola) ALTERNATIVE HYPOTHESIS H1: p > 0.50 (exceeding 50%) 3. COMPUTATION OF POPULATION PARAMETER: σ = STANDARD DEVIATION = sqrt[ p * ( 1 - p) / n ] n = SAMPLE SIZE [200] σ = sqrt [0.50 * (1 - 0.50)/200] = (approx.) 0.0354 4. COMPUTATION OF TEST STATISTIC ("critical value of z") z = (p_hat - p) / σ p_hat = SAMPLE PROPORTION [0.55] (55%) z = (0.55-0.50)/ 0.0354 = 0.9177 = (approx.) 1.41 Valid when both conditions true: n * p > 10 [200 * 0.50 = 100 > 10] TRUE n (1 − p) > 10 [200 * (1 - 0.50) = 100 > 10] TRUE 5. "P-value" "Look-up" value of Normal Distribution "area under the curve" "to the right" of z = 1.41 "P-value" = 0.0787 6. TEST of P-value P-value > α (significance level) [0.0787 > 0.05]; Cannot reject NULL HYPOTHESIS stating p = 0.50 (50% perfer Coca-Cola) "When P-value is low, let it go" (let go the NULL HYPOTHESIS) P-value ≤ α "When P-value is high, let it fly" (let fly the NULL HYPOTHESIS) P-value > α 7. CONCLUSION: For signficance level α = 0.05, NULL HYPOTHESIS H0: p = 0.50 (50% prefer Coca-Cola) is accepted. Coca-Cola is equally preferred and not preferred over other brands.
Statistics help PLEASE!!?
If you multiply the frequency by the mean of the weight range for each of the 7 rows, then divide by the total number of skittles (430) you get 1.059 which is answer a) For instance. (0.755 + 0.814) / 2 = .7845 (0.815 + 0.874) / 2 = .8445 (0.875 + 0.934) / 2 = .9045 etc. so multiplying each by frequency is: .7845 (3) + .8445 (2) + .9045 (2) + etc. divide total by 430 The variance = 0.001924978 (from excel VARP function on a column of the results)
Statistics help please!?
The first letter must be K or W, so there are 2 possible options. The next two letters can be from any of the letters, so there are 26 possible options for each. The last letter is optional, so it can be A-Z or nothing, for a total of 27 possible options. Multiply them together to get: 2 * 26² * 27 = 36,504 different possible call letters for a radio station. Factorial really only matters when there is no duplication of letters, so really not needed in this example.
Statistics help please math wiz! Thanks.?
The final exam in a one-term statistics course is taken in the december exam period. Students who are sick or have other legitimate reasons for missing the exam are allow to writte a deferred exam scheduled for the first week in January. A statistics professor has observed that only 2% of all students legitimately miss the December final exam. Suppose that the professor has 40 students registered this term. a) How many students can the professor expect to miss the December exam? b) What is the probability that the professor will not have to create a deferred exam?
Statistics help please?
A canoe club sponsor has taken canoeing groups through a particularly rough section of white water on a mountain river. Past trips and experience of the sponsor lead her to believe that 55% of the canoeists who attempt to paddle their way through this section will overturn. At the present time, there are 5 canoes approaching this treacherous section. Assume that the sponsor's estimate of the probability of a canoe overturning in this section of water is accurate. What is the standard deviation of the number of canoes that will capsize? s.d. =
Statistics help please?
Take your table of z-scores (you have one, don't you?) and find the z-score that corresponds to .3400. That represents 34% of the distribution between the mean and z (on ONE SIDE of the distribution only!). WHY 34%?? because 50% -16% = 34%, and we're looking at one side, or one half, of the distribution only). You should find that the z-score is very close to 1. So it's clear that those two symmetrical 34% parts of the distribution nearest the mean (total: 68%) are 1 standard deviation from the mean, and that must correspond to a standard deviation of 20. The remaining 32% falls outside 1 standard deviation, but it's divided into two parts: 16% below 1 SD, and the other 16% above 1 SD.
How do you use statistics in your job?
Edit: The question title was "How is statistics used in real life?" when I wrote this, and that's the question I was addressing.I always struggle with these sorts of questions, because there are two different ways to interpret what's being asked, and the answers often have very little in common. But I think that here it's reasonable to spell out what those questions are, and to give the answers to both of them.The first reading is "How will the average person use statistics?", and the answer is that by and large they won't. Sure, they might have to interpret basic descriptive statistics like means and medians, but they're just not doing anything that requires tools which are more sophisticated than that. Heck, even I don't really do any serious statistics off the clock.The second reading is "How are statistics used outside of a statistics class?", and the answer is that almost every non-trivial technical problem requires some degree of statistical analysis, and the techniques you need to use are often quite complicated even if the problems are simple. Deciding which of two surgical procedures gives a better outcome for a certain type of cancer is an active research area, and the techniques that are just now coming out are showing up in practice pretty quickly.As others have mentioned, one of the key activities of statistics is prediction. What will the weather be like tomorrow? How many units of this product will we sell next month? Which of these ten links are you most likely to click on? Will there be a major earthquake in San Francisco within the next ten years? You can pretty easily see why these questions are interesting to their respective audiences, and every single one of them requires statistical methods to answer.
STATISTICS HELP PLEASE (sample means etc)?
1.According to the central limit theorem, since the sample size of n=64 is large(the thumb of the rule is at least equal to or greater than 30), then the sample mean-x-bar should be approximately close to the population mean, U of 500. 2. According to the central limit theorem, since the sample size of n=64 is large(the thumb of the rule is at least equal to or greater than 30), then the standard deviation of the mean of the sample means is δx-bar=δ/√n = 100/√64 = 12.5 from the population mean. 3.According to the central limit theorem, since the sample size of n=64 is large(the thumb of the rule is at least equal to or greater than 30), then the sampling distribution of sample means of scores on the GRE quantitative subtest-x-bar will have a symmetrical bell-shape which follow the z standard normal distribution. Hope this helps.