A hypothesis (pl.: hypotheses) is a proposed explanation for a phenomenon. For a hypothesis to be a scientific hypothesis, the scientific method requires that one can test it. Scientists generally base scientific hypotheses on previous observations that cannot satisfactorily be explained with the available scientific theories. Even though the words "hypothesis" and "theory" are often used interchangeably, a scientific hypothesis is not the same as a scientific theory. A working hypothesis is a provisionally accepted hypothesis proposed for further research in a process beginning with an educated guess or thought.
A different meaning of the term hypothesis is used in formal logic, to denote the antecedent of a proposition; thus in the proposition "If P, then Q", P denotes the hypothesis (or antecedent); Q can be called a consequent. P is the assumption in a (possibly counterfactual) What If question. The adjective hypothetical, meaning "having the nature of a hypothesis", or "being assumed to exist as an immediate consequence of a hypothesis", can refer to any of these meanings of the term "hypothesis".
Placebo/control group has 800 people. They aren't given the vaccine. 60 of them develop the disease
Treatment group has 1000 people. They're given the vaccine. 15 develop the disease
It seems there's a formula viz ##\frac{p_1 - p_2}{\sqrt{p (1 - p)}\left(\frac{1}{n_1} + \frac {1}{n_2}\right)}##...
My attempt:
a) I am not really sure I understand this option fully but my answer will be this one is only applicable if the sample size is large and central limit theorem can be applied so (a) is wrong
b) The test statistic has "same distribution" to what? My opinion is (b) is wrong because...
##H_0##: The probability of an obese person using chopsticks = the probability of a normal-weight person using chopsticks
##H_a##: The probability of an obese person using chopsticks ##\ne## the probability of a normal-weight person using chopsticks
"Partial" Chi-Square Test: I focused only on...
TL;DR Summary: Sims and sample size
A statistics question I have in my notes goes like this:
Our significance level ##\alpha = 0.01##
The percentage of left-handed people in the general population is ##10\%##. Liliana is curious if this is true for her arts class and so she takes a random...
Reached Hypothesis testing in my statistics notes (high school level).
It reads ...
1. Type I Error: Rejecting the null (hypothesis), ##H_0##, when ##H_0## is true. The risk of a Type I error can be reduced by lowering the significance level ##\alpha##. The downside is this increases the...