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   "source": [
    "# Practicum 3 Review - Key Concepts"
   ]
  },
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   "source": [
    "## Logistics"
   ]
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   "source": [
    "- 1000 - 1150 on Wednesday, May 7th in Herrick 313\n",
    "- The format will be the same as the other practicums\n",
    "- The practicum is comprehensive with an emphasis on Chapters 13 thru 17"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aaf6169f-5a3e-40c3-9f60-feede2882220",
   "metadata": {},
   "source": [
    "## Chapter 13 - Estimation"
   ]
  },
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   "source": [
    "- percentile function (first quartile, median, third quartile)\n",
    "- bootstrap method (resampling from the sample)\n",
    "- confidence interval\n",
    "- using confidence intervals to test a null hypothesis (or alternative hypothesis)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc8c0bd4-ffe1-42d5-b03c-e813156e3801",
   "metadata": {},
   "source": [
    "## Chapter 14 - Why the Mean Matters"
   ]
  },
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   "id": "04d9a693-51e7-4902-b84d-545770b41da3",
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    "- mean\n",
    "- standard deviation\n",
    "- standard units\n",
    "- normal curve (and cdf function)\n",
    "- Central Limit Theorem\n",
    "- Central Limit Theorem for Sample Mean (SD of all sample means = population SD / sqrt(sample size)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f50d1aa2-2b9a-4a21-8c41-feba54a71168",
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   "source": [
    "## Chapter 15 - Prediction"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32d60762-5b9a-4620-b116-8ba9106f6b9d",
   "metadata": {},
   "source": [
    "- Correlation coefficient, r\n",
    "- Determining the regression line\n",
    "- Root Mean Square Error\n",
    "- minimize function\n",
    "- Residual (and visual diagnostics)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eeaa75f4-42b4-4e16-a887-2103f3517ba3",
   "metadata": {},
   "source": [
    "## Chapter 16 - Inference for Regression"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "07772741-a705-46c7-ac7c-8fce7359d186",
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   "source": [
    "- Estimating the true slope\n",
    "- Making predictions\n",
    "- Bootstrap prediction intervals"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14cd6c10-2b98-460c-8c9e-46e4db0cec48",
   "metadata": {},
   "source": [
    "## Chapter 17 - Classification"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd32c5d6-2a99-45e2-9369-dd2a1b856803",
   "metadata": {},
   "source": [
    "- K-Nearest Neighbors\n",
    "- Distance between points\n",
    "- Testing data vs. training data\n",
    "- Measuring accuracy of classifier"
   ]
  }
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