The book of Genesis narrates the creation of the first man and woman, and the family is portrayed as having a central role in creation. Other Old Testament books speak of the love to be found in the family, which is also where children are taught wisdom and the virtues.
Definition[ edit ] In statisticsa null hypothesis is a statement that one seeks to nullify with evidence to the contrary.
Most commonly it is a statement that the phenomenon being studied produces no effect or makes no difference. An example of a null hypothesis is the statement "This diet has no effect on people's weight. Usually a type I error leads one to conclude that a supposed effect or relationship exists when in fact it doesn't.
Examples of type I errors include a test that shows a patient to have a disease when in fact the patient does not have the disease, a fire alarm going on indicating a fire when in fact there is no fire, or an experiment indicating that a medical treatment should cure a disease when in fact it does not.
Examples of type II errors would be a blood test failing to detect the disease it was designed to detect, in a patient who really has the disease; a fire breaking out and the fire alarm does not ring; or a clinical trial of a medical treatment failing to show that the treatment works when really it does.
Thus a type I error is a false positive, and a type II error is a false negative. When comparing two means, concluding the means were different when in reality they were not different would be a Type I error; concluding the means were not different when in reality they were different would be a Type II error.
Various extensions have been suggested as " Type III errors ", though none have wide use. In practice, the difference between a false positive and false negative is usually not obvious, since all statistical hypothesis tests have a probability of making type I and type II errors.
These error rates are traded off against each other: For a given test, the only way to reduce both error rates is to increase the sample size, and this may not be feasible. A test statistic is robust if the Type I error rate is controlled. These terms are also used in a more general way by social scientists and others to refer to flaws in reasoning.
Statistical test theory[ edit ] In statistical test theory, the notion of statistical error is an integral part of hypothesis testing.
The test requires an unambiguous statement of a null hypothesis, which usually corresponds to a default "state of nature", for example "this person is healthy", "this accused is not guilty" or "this product is not broken".
An alternative hypothesis is the negation of null hypothesis, for example, "this person is not healthy", "this accused is guilty" or "this product is broken". The result of the test may be negative, relative to the null hypothesis not healthy, guilty, broken or positive healthy, not guilty, not broken.
If the result of the test corresponds with reality, then a correct decision has been made. However, if the result of the test does not correspond with reality, then an error has occurred. Due to the statistical nature of a test, the result is never, except in very rare cases, free of error.
Two types of error are distinguished: It is asserting something that is absent, a false hit. In terms of folk talesan investigator may see the wolf when there is none "raising a false alarm". Where the null hypothesis, H0, is: Often, the significance level is set to 0.
It is failing to assert what is present, a miss.
A Type II error is committed when we fail to believe a true alternative hypothesis.The family is ordained of God and is central to His plan for the eternal destiny of His children. This divine plan makes it possible for individuals to return to His presence and for families to be united eternally.
the Firstborn. INDEX: * The Rights of the Firstborn * Jesus Was the Firstborn * In What Ways Was Jesus the Firstborn? * Who Are the Firstborn Today? If you are looking for support, advice, safety information or referral to local services. Please call the Pippa Helpline (Monday-Friday pm).
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