Questions and Answers:
How does one insert a null value directly into a Field in a table in ms access?
Have a prisoner table. There are ten prisoners in total. I have a mobile number column. I need to have at least two prisoners with null for a mobile number. So do I leave it blank, type null or do something else?
Answer: Assuming the "required" property is set to "no" and "allow zero length" property is set to "yes", just skip it. If either of those are set otherwise (or your using a form that won't let you) fill it with S "000-000-0000".
What is the null and alternative hypothesis to this experiment?
, struggling on this question, so if you could help that would be great! I am studying whet here listening to music while learning the information, and also at other noise levels and without no music at all. So, could someone help me with the null and alternative hypothesis please
Answer: Let's see. The null hypothesis might be: listening to music while studying information has no eff etc on learning. The alternative hypothesis would be: listening to music while studying information improves learning. That should do it. Hope this helps, michael http://www. Psychedelia's. Com
What would be the null hypothesis and alternative hypothesis?
Inguinal statement: use a 0. 01 significance level to test the claim the old ratings are higher than the new ratings. This problem is based on ratings of movies. If that's the original claim, what would the null hypothesis and alternative hypothesis be? Also, would this one a one tail or two tail test?
Answer: Null hypothesis: old ratings = new ratings or (old ratings) - (new ratings) = 0 alternative hypothesis: old ratings > new ratings (old ratings) - (new ratings) > 0 right tail or new ratings < old ratings (new ratings) - (old ratings) < 0 left tail
What is the null hypothesis of 2 retailers?
Need to state a null hypothesis of examination of a local grocer and an Internet chain while examining 34 exact items and say whet here one is statistically different? Would the null be Kroger and net grocer are equal in price and the alternative be Kroger is statistically cheaper than netgrocer? Or do I need to state an actual amount of difference? Such as alternative Kroger is $100 cheaper than netgrocer?
Answer: My best guess: ho: the mean difference in product prices between the two retailers is zero. Ha: the mean difference in product prices between the two retailers is (less than, not equal to, greater than) zero. That way, if you reject the null hypothesis, you have enough difference between the prices at a statistically significant level.
. What is the difference between the null and alternative hypotheses statements in one-tailed and two-tailed t
At is the difference between the null and alternative hypotheses statements in one-tailed and two-tailed tests? How can manufacturing companies use the standard normal distribution to determine quality control of their products? 2. What is the "perfetc" standard normal distribution? Explain your answer. What value is business research and hypothesis testing to a company?
Answer: Consider the hypothesis as a trial against the null hypothesis. The data is evidence against the mean. You assume the mean is true and try to prove that it is not true. If the question statement asks you to determine if there is a difference between the statistic and a value, then you have a two tail test, the null hypothesis, for example, would be = d vs the alternate hypothesis d if the question ask to test for an inequality you make sure that your results will be worth while. For example. Say you have a steel bar that will be used in a construction project. If the bar can support a load of 100,000 psi then you'll use the bar, if it cannot then you will not use the bar. If the null was 100,000 vs the alternate < 100,000 then will will have a meaningless test. In this case if you reject the null hypothesis you will conclude that the alternate hypothesis is true and the mean load the bar can support is less than 100,000 psi and you will not be able to use the bar. However, if you fail to reject the null then you will conclude it is plausible the mean is greater than or equal to 100,000. You cannot ever conclude that the null is true. As a result you should not use the bar because you do not have proof that the mean strength is high enough. If the null was 100,000 vs. The alternate > 100,000 and you reject the null then you conclude the alternate is true and the bar is strong enough; if you fail to reject it is plausible the bar is not strong enough, so you don't use it. In this case you have a meaningful result. Any time you are defining the hypothesis test you need to consider whet here or not the results will be meaningful. === === you can use the standard normal in quality control because of the central limit theorem. Let X, X,... , Zn be a simple random sample from a population with mean and variance. Let Bar be the sample mean = 1/n * xi let Sn be the sum of sample observations: Sn = xi then, if n is sufficiently largee: xbar has the normal distribution with mean and variance / n xbar ~ normal( , / n) sn has the normal distribution with mean n and variance n sn ~ normal(n , n) the great thing is that it does not matter what the under lying distribution is, the central limit theorem holds. It was pr oven by Markov using continuing fractions. If the sample comes from a uniform distribution the sufficient sample size is as small as 12 if the sample comes from an exponential distribution the sufficient sample size could be several hundred to several thousand. If the data comes from a normal distribution to start with then any sample size is sufficient. For n < 30, if the sample is from a normal distribution we use the student t statistic to estimate the distribution. We do this because the student t takes into account the uncertainty in the estimate for the standard deviation. If we now the population standard deviation then we can use the z statistic from the beginning. The value of 30 was empirically defined because at around that sample size, the quartiles of the student t are close the quartiles of the standard normal. === === the perfect standard normal is normal( = 0, = 1). As n , Bar ~ normal(x , x / n) and (xbar - x ) / sqrt( x / n) ~ normal( = 0, = 1) because of this, in a sample of sufficient size we can approximate the behavior of the mean with the normal distribution which is easily translated into the standard normal. This is the basis for nearly all parametric hypothesis testing.
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