predictions and increasing success in providing highly precise and sur terjemahan - predictions and increasing success in providing highly precise and sur Bahasa Indonesia Bagaimana mengatakan

predictions and increasing success

predictions and increasing success in providing highly precise and surpris­ ing ones. On both these counts, [L] fares poorly. Beyond obvious predic­ tions, the application of [L] fares poorly. Even knowing a great deal about your family and friends, you cannot predict exactly what they will do next; you probably can't even predict roughly what they will do next, except in very stereotyped conditions. Strangely enough, most people have been well satisfied with [ L] for most of recorded history, despite its weakness. Only twentieth- century social and behavioral scientists have been troubled by their inability to improve [ L ] 's predictive power. But that's because [ L ] 's pre­ dictive weakness undermines the claim that it is a causal law and thus un­ dermines a scientific approach to human action.
It's clear that in order to improve our predictions of human action, we need to do either or both of two things: We need to be able to "measure" people's beliefs and desires with greater precision. And we need to improve [L] itself. For example, we need to develop models of rational choice that fill in [ L] ,s ceteris paribus-other things being equal-clause. That is how all causal explanations and causal laws are improved.
To see that, consider a model from physics: the ideal gas law, PV = nRT. Suppose we want to explain why the pressure gauge on the gas container reads 1 5.2885 atmospheres. To do so we measure the temperature with a thermometer, discovering it to be 99.5°C, and measure the volume of the container, discovering it to be 2.001 liters. When we plug the temperature and volume into the equation, the result is that the pressure is 1 5.3 1 0 1 . This value is probably close enough to the true value for most purposes. Indeed, all measuring instruments, thermometers, manometers, and metersticks, have margins for error. For all we know, the theoretically derived value for pressure may be closer to the real value than the pressure gauge's reading. How can we decide which is more accurate-the value predicted by plug­ ging the data into the equation or the value observed on the pressure gauge? The only way to decide is by improving our measuring instruments. Substi­ tute a thermometer that reads out digitally to more decimal places; a mi­ crometer instead of a meterstick to measure length, breadth, depth, for volume; and a digital pressure gauge instead of an anw.og dial. Any of these changes will help give more accurate measurements of the initial conditions. If the more accurate numbers provided by these new measuring instru­ ments are plugged into the equation, the resulting calculation may be much closer to the observed values. In other words, the precision of our explana­ tion will have been improved, and the accuracy of future predictions using the ideal gas law will also have been increased by these new instruments.
Even more important is what happens when improvements in measure­ ment of initial conditions do not result in calculated values closer to observed
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predictions and increasing success in providing highly precise and surpris­ ing ones. On both these counts, [L] fares poorly. Beyond obvious predic­ tions, the application of [L] fares poorly. Even knowing a great deal about your family and friends, you cannot predict exactly what they will do next; you probably can't even predict roughly what they will do next, except in very stereotyped conditions. Strangely enough, most people have been well satisfied with [ L] for most of recorded history, despite its weakness. Only twentieth- century social and behavioral scientists have been troubled by their inability to improve [ L ] 's predictive power. But that's because [ L ] 's pre­ dictive weakness undermines the claim that it is a causal law and thus un­ dermines a scientific approach to human action.It's clear that in order to improve our predictions of human action, we need to do either or both of two things: We need to be able to "measure" people's beliefs and desires with greater precision. And we need to improve [L] itself. For example, we need to develop models of rational choice that fill in [ L] ,s ceteris paribus-other things being equal-clause. That is how all causal explanations and causal laws are improved.To see that, consider a model from physics: the ideal gas law, PV = nRT. Suppose we want to explain why the pressure gauge on the gas container reads 1 5.2885 atmospheres. To do so we measure the temperature with a thermometer, discovering it to be 99.5°C, and measure the volume of the container, discovering it to be 2.001 liters. When we plug the temperature and volume into the equation, the result is that the pressure is 1 5.3 1 0 1 . This value is probably close enough to the true value for most purposes. Indeed, all measuring instruments, thermometers, manometers, and metersticks, have margins for error. For all we know, the theoretically derived value for pressure may be closer to the real value than the pressure gauge's reading. How can we decide which is more accurate-the value predicted by plug­ ging the data into the equation or the value observed on the pressure gauge? The only way to decide is by improving our measuring instruments. Substi­ tute a thermometer that reads out digitally to more decimal places; a mi­ crometer instead of a meterstick to measure length, breadth, depth, for volume; and a digital pressure gauge instead of an anw.og dial. Any of these changes will help give more accurate measurements of the initial conditions. If the more accurate numbers provided by these new measuring instru­ ments are plugged into the equation, the resulting calculation may be much closer to the observed values. In other words, the precision of our explana­ tion will have been improved, and the accuracy of future predictions using the ideal gas law will also have been increased by these new instruments.Even more important is what happens when improvements in measure­ ment of initial conditions do not result in calculated values closer to observed
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prediksi dan meningkatkan keberhasilan dalam memberikan yang sangat tepat dan surpris ing yang. Pada kedua hal ini, [L] tarif buruk. Di luar tions predic jelas, penerapan [L] tarif buruk. Bahkan mengetahui banyak tentang keluarga dan teman-teman, Anda tidak dapat memprediksi apa yang akan mereka lakukan selanjutnya; Anda mungkin bahkan tidak dapat memprediksi kira-kira apa yang akan mereka lakukan selanjutnya, kecuali dalam kondisi yang sangat stereotip. Anehnya, kebanyakan orang telah puas dengan [L] untuk sebagian besar catatan sejarah, meskipun kelemahannya. Hanya para ilmuwan sosial dan perilaku abad kedua puluh telah terganggu oleh ketidakmampuan mereka untuk meningkatkan [L] 's daya prediksi. Tapi itu karena [L] 's kelemahan predictive pra merusak klaim bahwa itu adalah hukum sebab akibat dan dengan demikian un dermines pendekatan ilmiah untuk tindakan manusia.
Sudah jelas bahwa dalam rangka meningkatkan prediksi kami tindakan manusia, yang perlu kita lakukan baik atau kedua dari dua hal: Kita perlu untuk dapat "mengukur" keyakinan rakyat dan keinginan dengan lebih presisi. Dan kita perlu meningkatkan [L] itu sendiri. Sebagai contoh, kita perlu mengembangkan model pilihan rasional yang mengisi [L], hal s ceteris paribus-lainnya sama-klausul. Itu adalah bagaimana semua penjelasan kausal dan hukum sebab akibat ditingkatkan.
Untuk melihat bahwa, mempertimbangkan model dari fisika: hukum gas ideal, PV = nRT. Misalkan kita ingin menjelaskan mengapa pengukur tekanan pada wadah gas berbunyi 1 5,2885 atmosfer. Untuk melakukannya kita mengukur suhu dengan termometer, menemukan itu menjadi 99,5 ° C, dan mengukur volume wadah, menemukan itu menjadi 2,001 liter. Ketika kita pasang suhu dan volume ke dalam persamaan, hasilnya adalah bahwa tekanan adalah 1 5.3 1 0 1. Nilai ini mungkin cukup dekat dengan nilai sebenarnya untuk sebagian besar tujuan. Memang, semua alat ukur, termometer, manometer, dan metersticks, memiliki margin untuk kesalahan. Untuk semua kita tahu, nilai teoritis yang diperoleh untuk tekanan mungkin lebih dekat dengan nilai sebenarnya dari bacaan pengukur tekanan ini. Bagaimana kita bisa memutuskan mana yang lebih akurat-nilai yang diperkirakan oleh steker ging data ke dalam persamaan atau nilai yang diamati pada pengukur tekanan? Satu-satunya cara untuk memutuskan adalah dengan meningkatkan alat ukur kami. Substi tute termometer yang membacakan secara digital untuk tempat desimal lebih; a crometer mi bukannya meteran untuk mengukur panjang, lebar, kedalaman, untuk volume; dan tekanan digital mengukur bukannya dial anw.og. Setiap perubahan ini akan membantu memberikan pengukuran yang lebih akurat dari kondisi awal. Jika angka yang lebih akurat yang disediakan oleh KASIH pengukuran instrumen baru yang dipasang ke dalam persamaan, perhitungan yang dihasilkan mungkin lebih dekat dengan nilai-nilai yang diamati. Dengan kata lain, ketepatan tion Pemaparan kami akan telah diperbaiki, dan akurasi prediksi masa depan dengan menggunakan hukum gas ideal juga telah meningkat instrumen baru.
Yang lebih penting adalah apa yang terjadi ketika perbaikan dalam ukuran ment dari kondisi awal tidak menghasilkan nilai dihitung lebih dekat dengan yang diamati
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