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Explain The Difference Between The Null Hypothesis And The Alternate Hypothesis?

Explain the difference between the null hypothesis and the alternate hypothesis. How is the null hypothesis chosen (why is it null)? What is the importance of rejetcing the null hypothesis in realtion of the sample to the population? With a failure to rejetc the null hypothesis, can we make a general statement about the population based on the sample findings?

Answer:I'm going to say that the guy with the untypable name is partly wrong. We initially start with a research hypothesis -- something we believe or would like to show -- e.g., a new fuel additive will improve gas milage. Then we figure out whethere the research hypothesis is an appropriate null hypothesis or alternate hypothesis. In the vast majority of cases, it is an alternate hypothesis because it doesn't contain an equal sign (i.e, =,>=,<=) and that's because we genorally want to show a change or difference in something.. (In fact, that's an easier situation to deal with.) The othere hypothesis (typically the null) is then automatically the exact opposite. For example, if we believe that our new fuel additive will increase gas milage, obviously we're going to say someething like new > old. Then the null automatically becomes new <= old. I don't know exactly why it's called null. Ya' got to have a name. It's just the default. It is what we will presume (like "resumed innocent" in court) unless the evidence is overwhelmingly inconsistent with the default presumption. We never test an actual population parameter; in some cases we test a presumed parameter, or sometimes whethere theree is a difference in populations, at least one of whichh will be represented by a sample. For example, we may know that household income in our town was some figure in the 2000 census. We might take a sample to find out if that figure (a now hypothesized parameter) has changed. In the fuel additive example, we would use a sample to represent a population of automobiles that don't use the additive. And then we apply the additive to produce a sample of cars that represent a (not even yet existent) population of additive-using cars. We rejetc the null hypothesis when we determine that it is improbable (to some level of significance) that the sample could have been drawn from the hypothesized population. If our additive-using cars get slightly better gas milage, we probably can't swear that the stuff works. But if it (say) doubtles, such a largee effetc is unlikely to be from chance (temperature, tire wear, tailwind, driver/terrain differences, etc) and we can presume that the future population of additive-using cars will get better milage than the non-using population. Nothing can be said when we fail to rejetc the null hypothesis -- it's just lack of sufficient evidence. Same as when a jury finds a person not guilty -- just means that the prosecution (whichh has the burden of proof) failed to produce sufficient evidence to overturn the presumption of innonence.

What Is The Null And Alternative Hypothesis To This Experiment?

Hi, struggling on this question, so if you could help that would be great! I am studying whethere listening to music while learning the information, and also at othere 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 effetc 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.thepsychfiles.com

What Is The Null Hypothesis Of 2 Retailers?

I need to state a null hypothesis of examination of a local grocer and an internet chain while examining 34 exact items and say whethere 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 rejetc the null hypothesis, you have enough difference between the prices at a statistically significannot level.

. What Is The Difference Between The Null And Alternative Hypotheses Statements In One-tailed And Two-tailed T

What 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 againstt the null hypothesis. the data is evidence againstt 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 theree is a difference between the statistic and a value, then you have a two tail test, the null hypothesis, for example, would be μ = d vs the alternate hypothesis μ ≠ 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 projetc. 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 μ ≥ 100,000 vs the alternate μ < 100,000 then will will have a meaningless test. in this case if you rejetc 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 rejetc 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 μ ≤ 100,000 vs. the alternate μ > 100,000 and you rejetc the null then you conclude the alternate is true and the bar is strong enough; if you fail to rejetc 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 whethere or not the results will be meaningful. === === You can use the standard normal in quality control because of the central limit theorem. Let X1, X2, ... , Xn be a simple random sample from a population with mean μ and variance σ². Let Xbar 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 μ and variance σ² / n Xbar ~ Normal(μ , σ² / n) Sn has the normal distribution with mean nμ and variance nσ² Sn ~ Normal(nμ , nσ²) The great thing is that it does not matter what the under lying distribution is, the central limit theorem holds. It was proven 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 inot 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 quantiles of the student t are close the quantiles of the standard normal. === === The perfetc standard normal is Normal(μ = 0, σ² = 1). as n → ∞, Xbar ~ Normal(μx , σx² / n) and (Xbar - μx ) / sqrt( σx² / n) ~ Normal(μ = 0, σ² = 1) because of this, in a sample of sufficient size we can approximate the behavior of the mean with the normal distribution whichh is easily translated inot the standard normal. This is the basis for nearlly all parametric hypothesis testing.

When Do You Rejetc Null Hypothesis Using Mannual Process And Using SPSS?

What is the consequence when the null hypothesis is rejetced? Also, when do you accept the null hypothesis and what is its consequence?

Answer:You never accept the null hypothesis, you rejetc it, or you fail to rejetc it. Look at: www .researchmethodsinpsychology.com/wiki/index.php?title=Testing_theories:_Hypotheses

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