Null hypothesis: Béda antarrépisi
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Dina [[statistik]], '''hipotesis kosong''' (Ing: ''null hypotesis'') nyaéta hipotesis nu mibanda anggapan awal bener lamun kajadian statistik dina bentuk tes hipotesis nunjukkeun sabalikna. Hipotesis kosong nyaéta hiji hipotesis yén urang mikaresep kana hiji hal nu nembongkeun hal éta téh palsu atawa salah! Salawasna ieu katangtuan téh ngeunaan hiji [[parameter]] nu ngagambarkeun sifat tina hiji populasi,
Not unusually, such a hypothesis states that the [[parameter]]s, or mathematical characteristics, of two or more [[populasi statistik|populasi]] are identical. For example, if we want to compare the test scores of two random [[statistical sample|sample]]s of men and women, the null hypothesis would be that the méan score in the male population from which the first sample was drawn was the same as the méan score in the female population from which the second sample was drawn:
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In formulating a particular null hypothesis, we are always also formulating an '''alternative hypothesis''', which we will accept if the observed data values are sufficiently improbable under the null hypothesis. The precise formulation of the null hypothesis has implications for the alternative. For example, if the null hypothesis is that sample A is drawn from a population with the same méan as sample B, the alternative hypothesis is that they come from populations with ''different'' méans (and we shall proceed to a [[two-tailed test]] of significance). But if the null hypothesis is that sample A is drawn from a population whose méan is no lower than the méan of the population from which sample B is drawn, the alternative hypothesis is that sample A comes from a population with a ''larger'' méan than the population from which sample B is drawn, and we will proceed to a one-tailed test.
A null hypothesis is only useful if it is possible to calculate the probability of observing a data set with particular
If experimental observations contradict the prediction of the null hypothesis, it méans that either the null hypothesis is false, or we have observed an event with very low probability. This gives us high confidence in the falsehood of the null hypothesis, which can be improved by incréasing the number of trials. However, accepting the alternative hypothesis only commits us to a difference in observed
For example, rejection of a null hypothesis (that, say, rates of symptom relief in a sample of patients who received a [[placebo]] and a sample who received a medicinal drug will be equal) allows us to maké a non-null statement (that the rates differed); it does not prove that the drug relieved the symptoms, though it gives us more confidence in that hypothesis.
The formulation, testing, and rejection of null hypotheses is methodologically consistent with the [[falsificationism|falsificationist]]
In [[2002]], a group of psychologists launched a new journal dedicated to experimental studies in [[psychology]] which support the null hypothesis. The ''Journal of Articles in Support of the Null Hypothesis'' (JASNH) was founded to address a scientific publishing bias against such articles. [http://www.jasnh.com/] According to the editors,
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