Bernard Lamy was a 17th-century French
theologian and mathematician who published treatises on biblical studies
and mathematics. One of his most famous works is ‘Elements of
Mathematics’ in which he discusses aspects of basic arithmetic and
advanced algebra and geometry. This book, designed as a pedagogical
treatise, is filled with question and answer problems with explanations
and procedures on how to solve problems.f
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Bernard Lamy (15 June 1640, in Le Mans, France–29 January 1715, in Rouen, France) was a French Oratorian, mathematician and theologian.
Lamy became professor of classics at Vendôme in 1661, and at Juilly in 1663. He was ordained in 1667.
After teaching a few years at Le Mans he was appointed to a chair of philosophy in the University of Angers. Here his teaching was attacked on the ground that it was too exclusively Cartesian, and Rebous the rector obtained in 1675 from the state authorities a decree forbidding him to continue his lectures.
He was then sent by his superiors to Grenoble, where, thanks to the protection of Cardinal Le Camus, he again took up his courses of philosophy. In 1686 he returned to Paris, stopping at the seminary of Saint Magloire, and in 1689 he was sent to Rouen, where he spent the remainder of his days.
His writings are numerous and varied. Among them may be mentioned:
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Bernard Lamy
| Bernard Lamy | |
|---|---|
Portrait
|
|
| Born | 15 June 1640 Le Mans |
| Died | 29 January 1715 (aged 74) Rouen |
| Residence | France |
| Nationality | French |
| Known for | Parallelogram of force |
| Scientific career | |
| Fields | Mathematics |
| Institutions | College of Juilly, University of Angers |
Contents
Life
After studying in Le Mans, he went to join the Maison d'Institution in Paris, and to Saumur thereafter. In 1658 he entered the congregation of the Oratory.Lamy became professor of classics at Vendôme in 1661, and at Juilly in 1663. He was ordained in 1667.
After teaching a few years at Le Mans he was appointed to a chair of philosophy in the University of Angers. Here his teaching was attacked on the ground that it was too exclusively Cartesian, and Rebous the rector obtained in 1675 from the state authorities a decree forbidding him to continue his lectures.
He was then sent by his superiors to Grenoble, where, thanks to the protection of Cardinal Le Camus, he again took up his courses of philosophy. In 1686 he returned to Paris, stopping at the seminary of Saint Magloire, and in 1689 he was sent to Rouen, where he spent the remainder of his days.
Works
His best known work is the Traité de Mécanique (1679), showing the parallelogram of force. He also wrote Traité de la grandeur en general (1680) and Les éléments de géometrie (1685).His writings are numerous and varied. Among them may be mentioned:
- "La Rhétorique ou l'art de parler", (Paris, 1675, Rhetoric, or the art of speaking, English translation 1676) of this twenty editions were published.[1]
- "Apparatus ad Biblia Sacra", etc. (Grenoble, 1687), translated into French by order of the Bishop of Châlons under the title "Introduction a la lecture de l'Ecriture Sainte" (Lyons, 1689).
- "Harmonia, sive Concordia quatuor Evangelistarum", a harmony or concordance of the Four Gospels (Paris, 1689). In this work he contends that John the Baptist was twice cast into prison, first in Jerusalem by order of the Sanhedrin, and later by Herod in Galilee. He maintains also that the Saviour and His Apostles did not eat the paschal lamb at the Last Supper, and that the Crucifixion occurred on the day on which the Jews celebrated the Passover. He considers Mary Magdalen, Mary the sister of Lazarus, and the sinner mentioned in Luke, vii, 37 sqq. to be one and the same person. These and other opinions involved him in controversy with Bulteau, pastor of Rouen, Jean Piénud, Le Nain de Tillemont, and others (see "Traité historique de l'ancienne Pâque des Juifs", Paris, 1693).
- "Apparatus Biblicus", which is a development of his introduction (Lyons, 1696; Jena, 1709; Amsterdam, 1710). It was translated into French by Abbé de Bellegarde (Paris, 1697) and by Abbé Boyer (Lyons, 1709). In this work he calls in question the historical character of the book of Tobias and book of Judith, and maintains that even after the Council of Trent a difference of authority should be recognized between the proto-canonical and deutero-canonical books of the Bible.
- "Défense de l'ancien sentiment de l'Eglise latine touchant l'office de sainte Madeleine" (Rouen, Paris, 1697).
- A volume of commentaries on his previous harmony of the Four Gospels (Paris, 1699).
- A Latin treatise on the Ark of the Covenant (Paris, 1720), a posthumous work published by Père Desmollets, who prefixed to the volume a biography of the author.
Lami's theorem
In statics, Lami's theorem is an equation relating the magnitudes of three coplanar, concurrent and non-collinear forces, which keeps an object in static equilibrium, with the angles directly opposite to the corresponding forces. According to the theorem,
- where A, B and C are the numerical values of three coplanar, concurrent and non-collinear forces, which keep the object in static equilibrium, and α, β and γ are the angles directly opposite to the forces A, B and C respectively.
See also
Further reading
- R.K. Bansal (2005). "A Textbook of Engineering Mechanics". Laxmi Publications. p. 4. ISBN 978-81-7008-305-4.
- I.S. Gujral (2008). "Engineering Mechanics". Firewall Media. p. 10. ISBN 978-81-318-0295-3
Categories:
In 1908 William Sealy Gosset, an Englishman publishing under the pseudonym Student, developed the t-test and t distribution. The t distribution is a family of curves in which the number of degrees of freedom (the number of independent observations in the sample minus one) specifies a particular curve. As the sample size (and thus the degrees of freedom) increases, the t distribution approaches the bell shape of the standard normal distribution. In practice, for tests involving the mean of a sample of size greater than 30, the normal distribution is usually applied.
It is usual first to formulate a null hypothesis, which states that there is no effective difference between the observed sample mean and the hypothesized or stated population mean—i.e., that any measured difference is due only to chance. In an agricultural study, for example, the null hypothesis could be that an application of fertilizer has had no effect on crop yield, and an experiment would be performed to test whether it has increased the harvest. In general, a t-test may be either two-sided (also termed two-tailed), stating simply that the means are not equivalent, or one-sided, specifying whether the observed mean is larger or smaller than the hypothesized mean. The test statistic t is then calculated. If the observed t-statistic is more extreme than the critical value determined by the appropriate reference distribution, the null hypothesis is rejected. The appropriate reference distribution for the t-statistic is the t distribution. The critical value depends on the significance level of the test (the probability of erroneously rejecting the null hypothesis).
For example, suppose a researcher wishes to test the hypothesis that a sample of size n = 25 with mean = 79 and standard deviation s = 10 was drawn at random from a population with mean μ = 75 and unknown standard deviation. Using the formula for the t-statistic,
the calculated t equals 2. For a two-sided test at a common level of significance α = 0.05, the critical values from the t distribution on 24 degrees of freedom are −2.064 and 2.064. The calculated t
does not exceed these values, hence the null hypothesis cannot be
rejected with 95 percent confidence. (The confidence level is 1 − α.)
A second application of the t distribution tests the hypothesis that two independent random samples have the same mean. The t distribution can also be used to construct confidence intervals for the true mean of a population (the first application) or for the difference between two sample means (the second application). See also interval estimation.
In 1908 William Sealy Gosset, an Englishman publishing under the pseudonym Student, developed the t-test and t distribution. The t distribution is a family of curves in which the number of degrees of freedom (the number of independent observations in the sample minus one) specifies a particular curve. As the sample size (and thus the degrees of freedom) increases, the t distribution approaches the bell shape of the standard normal distribution. In practice, for tests involving the mean of a sample of size greater than 30, the normal distribution is usually applied.
It is usual first to formulate a null hypothesis, which states that there is no effective difference between the observed sample mean and the hypothesized or stated population mean—i.e., that any measured difference is due only to chance. In an agricultural study, for example, the null hypothesis could be that an application of fertilizer has had no effect on crop yield, and an experiment would be performed to test whether it has increased the harvest. In general, a t-test may be either two-sided (also termed two-tailed), stating simply that the means are not equivalent, or one-sided, specifying whether the observed mean is larger or smaller than the hypothesized mean. The test statistic t is then calculated. If the observed t-statistic is more extreme than the critical value determined by the appropriate reference distribution, the null hypothesis is rejected. The appropriate reference distribution for the t-statistic is the t distribution. The critical value depends on the significance level of the test (the probability of erroneously rejecting the null hypothesis).
For example, suppose a researcher wishes to test the hypothesis that a sample of size n = 25 with mean = 79 and standard deviation s = 10 was drawn at random from a population with mean μ = 75 and unknown standard deviation. Using the formula for the t-statistic,
the calculated t equals 2. For a two-sided test at a common level of significance α = 0.05, the critical values from the t distribution on 24 degrees of freedom are −2.064 and 2.064. The calculated t
does not exceed these values, hence the null hypothesis cannot be
rejected with 95 percent confidence. (The confidence level is 1 − α.)A second application of the t distribution tests the hypothesis that two independent random samples have the same mean. The t distribution can also be used to construct confidence intervals for the true mean of a population (the first application) or for the difference between two sample means (the second application). See also interval estimation.
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