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The common distributions

Bernoulli, binomial, Poisson, uniform, exponential, normal, and what each models.

Binomial counts successes; Poisson counts rare events; exponential waits for the next one; normal is what sums look like. Picture it: the bell curve and the 95% between ±1.96. Think it: the normal appears because of the central limit theorem, not because nature prefers it.

कार्यरत उदाहरण · integrate e^(-x^2/2)/sqrt(2*pi) dx from -1.96 to 1.96

Integrate sqrt(2)·e^(-x^2/2)/(2·sqrt(pi)) from -1.96000 to 1.96000

\int_{-1.96}^{1.96} \frac{\sqrt{2} e^{- \frac{x^{2}}{2}}}{2 \sqrt{\pi}}\, dx

चरणानुक्रमे

  1. \int_{-1.96}^{1.96} \frac{\sqrt{2} e^{- \frac{x^{2}}{2}}}{2 \sqrt{\pi}}\, dx

    First find an antiderivative F, then evaluate F(b) − F(a).

  2. \int \frac{\sqrt{2} e^{- \frac{x^{2}}{2}}}{2 \sqrt{\pi}}\, dx = \frac{\sqrt{2}}{2 \sqrt{\pi}} \int e^{- \frac{x^{2}}{2}}\, dx

    Pull the constant \frac{\sqrt{2}}{2 \sqrt{\pi}} out of the integral.

  3. \int e^{- \frac{x^{2}}{2}}\, dx = \frac{\sqrt{2} \sqrt{\pi} \operatorname{erf}{\left(\frac{\sqrt{2} x}{2} \right)}}{2}

    Erf rule.

  4. F(1.96) - F(-1.96) = \left(\frac{\operatorname{erf}{\left(0.98 \sqrt{2} \right)}}{2}\right) - \left(- \frac{\operatorname{erf}{\left(0.98 \sqrt{2} \right)}}{2}\right)

    Fundamental theorem of calculus: plug in the limits.

  5. = \operatorname{erf}{\left(0.98 \sqrt{2} \right)} \approx 0.95000

    Simplify.

उत्तर उघडा
\operatorname{erf}{\left(0.98 \sqrt{2} \right)}

आता तुम्ही प्रश्न निवडा, किंवा स्वतःचा प्रश्न टाइप करा किंवा रेखाटून दाखवा. प्रत्येक टप्प्यात, चित्रे आहेत, तुम्ही विचारण्याआधी उत्तर लपवलेले आहे.

स्वतःचे कार्य चालू ठेवा

मोफत खाते प्रत्येक शिकवणी वर टिपण्णी जोडते, तुम्ही पूर्ण केलेल्या गोष्टीचा नोंदवही, तुमच्या सोडविलेल्या समस्या एका ठिकाणी, आणि या पानाच्या विषयी तुम्ही विचारू शकता अशा शिक्षकाला. गणित स्वतःच सर्वांसाठी खुले आहे, दाखलन झालेले असो किंवा नसो.

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कसे कराल: The common distributions

  1. First find an antiderivative F, then evaluate F(b) − F(a).
  2. Pull the constant \frac{\sqrt{2}}{2 \sqrt{\pi}} out of the integral.
  3. Erf rule.
  4. Fundamental theorem of calculus: plug in the limits.
  5. Simplify.

लोक विचारतात ते प्रश्न

What is the difference between probability and statistics?

Probability goes from a known model to what the data should look like; statistics goes from data back to the model. Probability theory is the deductive half.

What does the law of large numbers promise?

That the average of many independent samples converges to the expected value. It says nothing about any single trial.

अधिक माहिती Probability Theory