Translation of "some probability" to Japanese language:
Examples (External sources, not reviewed)
| So the homework assignment will cover this plus some very basic probability. Probability | 第1問では基本的な確率の問題を解いてもらいます |
| There's some probability that we even get minus a thousand. | 別の直感的なものが本当にセンスが必要 |
| Probability | 確率 |
| I don't know why it's not exact. There's some sort of probability there. | Okay, let's take a look at this. |
| Some have 0.13, but the one over here has a probability of 0.533. | センサ確率を1 0つまりノイズなしにセットしたら |
| And I'll show you, we'll do some pretty complicated examples using probability tree. | 紹介しましょう ここでは 黄色で丸をした特別な理由はありません |
| So the probability, if you have a mean of minus 5 and a standard deviation of 10, the probability of getting a thousand here is very low but there's some probability. | 10 の標準偏差を得ることの確率 千ここは非常に低いですが いくつかの確率 おそらくいくつかはちょうど私の体の原子のすべてを |
| Their probability | 1回目が裏で 2回目が表で 3回目が裏の確率です |
| We start off and we imagine we have some graph with n nodes or we have some set of n nodes, and we have some probability p, which we'll call the connectivity probability and the generation process works like this. | 確率pがあります これを接続確率と呼びましょう 次の方法で作ります まずn個のノードだけを作り |
| Some people think what's the probability that land within one standard deviation of the mean? | 1 つの標準偏差の平均のですか まあ それは簡単に実行できます |
| So, that can't be true and the probability of some ranges of proportions become small. | 5番目の選択肢は正解です もっと起こりそうもないことから考えてみます |
| Probability of success | 成功確率 |
| Probability of failure | 失敗確率 |
| Probability first green | 起こりうる全ての場合の数は |
| Question 1 In the first question, I'm going to ask you some very basic probability questions. | 任意の確率変数Xがあり確率は0 2です |
| And it makes much more sense to talk about the probability or random variable equaling a value, or the probability that it is less than or greater than something or the probability that is has some property | 確率変数がある値に等しい確率 とか ある値より大きい(または小さい)確率 あるいは 確率変数が特定の性質を持つ確率 |
| Times the probability of b divided by the probability of a. | 割る aの確率となります そしてこれは ベイズ理論 あるいはベイズ法と呼ばれています |
| 0.5 probability being in A times 0.5 probability of remaining in A plus 0.5 probability to be in B times 1 probability to transition to A. | Bにいる確率0 5に Aへ遷移する確率1を掛けた値を足します 答えは0 75です |
| If I now change some parameters say the robot knows the probability that it's red, and therefore, the probability 1 is under the green cell as a prior. | そうすると緑の事前確率は1になります それではベイズの定理を使って 事後確率を求めてください |
| There's some probability he goes back, but there's still more particles,more sugar particles here than there. | こっち側より たくさんの砂糖分子がある なので 左側のやつが右に移動する可能性の方が |
| Are there some ranges of proportions for which the probability becomes small as we have many flips. | 表が出る確率が0でも1でもない値だとして 該当するものすべてにチェックしてください |
| There's some sort of a prior, of which we mean the probability before you run a test, and then you get some evidence from the test itself. and that all leads you to what's called a posterior probability. | つまりある試行をする前の確率のことで その試行からいくつかの証拠を得ます そしてそこから事後確率と呼ばれるものを導きます |
| Probability of finishing before | この日より前に終了する可能性 |
| Let's think about probability. | もし誰かに箱を開けて |
| That probability is 0.002. | i 1にwoeがある時 iにisが現れる確率は0 07です |
| So what's that probability? | 単に すべての結果を見るなら |
| What is the probability... | では 黄色のキューブを得る確率は何でしょうか |
| What is the probability, | では黄色かキューブである物の確率は何でしょうか |
| My resulting probability will be 1 α of the non normalized probability. | これがまさにベイズの定理です |
| The probability of any random variable Y can be written as probability of Y given that some other random variable X assumes value i times probability of X equals i, sums over all possible outcomes i for the (inaudible) variable X. | 確率変数Xiを条件とするYの確率に Xiの確率を掛けます そして確率変数Xのすべてのiについて すべての値を合計します |
| So that tells us the probability of a given b times the probability of b, is equal to the probability of b given a, times the probability of a. | 掛ける bの確率 イコール aを条件とするbの確率 掛ける aの確率と告げています そして この両方をaで割るならば |
| With probability Q, O plays 1, and with probability 1 Q plays 2. | そして1 qの確率で2を出します Eは得点を最大化したいので |
| So the probability of a given b could be the probability of a. | これは bに完全に依存していないかもしれません ですが それを知る方法はありません |
| lot where they say the probability sometimes it's written as probability of a. | ときには aの確率はPreb(a)と書かれます ときには 単にP(a)と書かれます |
| And we want to find interval of T values between some negative value here and some positive value here that contains 95 of the probability. | 確率の 95 が含まれている区間を 見つけます これが 95 です |
| They're not rational about probability. | プレイヤーはこのゲームは不公平だと考えます |
| One is about complementary probability. | ある事象が確率pを持っているのであれば |
| Probability of X2 equals heads. | 2通りのパターンがあります |
| labeled anything, with any probability. | そして 尤度 という関数を書いてもらいます |
| What's the probability of Y? | ここでは全確率の定理を使います |
| The probability is 5 32. | では もう少し複雑な例をやりましょう |
| Here we apply total probability. | x₂である確率はx₁から得られると思われる すべての状態を調べ |
| Now, what is the probability | これは少しややこしい問題かもしれないね |
| That is just total probability. | 次に条件付き独立性を活用します |
| That's called a probability histogram. | このサンプルの平均の分布です |
Related searches : With Some Probability - Probability Level - Probability Sampling - Marginal Probability - Probability Sample - Occurrence Probability - Probability Mass - Transition Probability - Reasonable Probability - Failure Probability - Cumulative Probability - Probability Plot - Default Probability
