Test_a_Perceptual_Phenomenon_20180507.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Analyzing the Stroop Effect\n",
    "\n",
    "\n",
    "We Perform the analysis in the space below according to [the instructions](https://docs.google.com/document/d/1-OkpZLjG_kX9J6LIQ5IltsqMzVWjh36QpnP2RYpVdPU/pub?embedded=True) and the [project rubric](https://review.udacity.com/#!/rubrics/71/view). \n",
    "\n",
    "\n",
    "(1) What is the independent variable? What is the dependent variable?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**_Answer_**\n",
    "\n",
    "\n",
    "The independent variable is the color of the ink in which the word is printed, whereas dependent variable is the time it takes to name the ink colors."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(2) What is an appropriate set of hypotheses for this task? Specify the null and alternative hypotheses, and clearly define any notation used. Justify the choices."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**_Answer_**\n",
    "\n",
    "\n",
    "The hypothesis regarding current test is that incongruent words requires more time for recognition as the words displayed are color words whose names do not match the colors in which they are printed, which call for extra efforts to tell.\n",
    "\n",
    "\n",
    "The null hypothesis is that the average time spent on identifing the colour of incongruent words will be no longer than that of congruent words, and the alternative hypothesis would be the average time spent on identifing the colour of incongruent words will be longer than that of congruent words.\n",
    "\n",
    "\n",
    "$ H_0: $ There is no difference in population means of response time under incongruent and congruent conditions ( $ H_0: μC = μI $).\n",
    "\n",
    "\n",
    "$ H_1: $ Population mean of the response time under incongruent condition will be significantly larger than the response time under congruent condition ( $ H_1: μC < μI $ ).\n",
    "\n",
    "\n",
    "http://support.minitab.com/en-us/minitab/17/topic-library/basic-statistics-and-graphs/hypothesis-tests/basics/null-and-alternative-hypotheses/\n",
    "\n",
    "\n",
    "http://support.minitab.com/en-us/minitab/17/topic-library/basic-statistics-and-graphs/hypothesis-tests/basics/what-is-a-hypothesis-test/\n",
    "\n",
    "\n",
    "http://support.minitab.com/en-us/minitab/17/topic-library/basic-statistics-and-graphs/hypothesis-tests/basics/directional-and-nondirectional-hypotheses/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(3) Report some descriptive statistics regarding this dataset. Include at least one measure of central tendency and at least one measure of variability. The name of the data file is 'stroopdata.csv'."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Congruent</th>\n",
       "      <th>Incongruent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12.079</td>\n",
       "      <td>19.278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>16.791</td>\n",
       "      <td>18.741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9.564</td>\n",
       "      <td>21.214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>8.630</td>\n",
       "      <td>15.687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>14.669</td>\n",
       "      <td>22.803</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Congruent  Incongruent\n",
       "0     12.079       19.278\n",
       "1     16.791       18.741\n",
       "2      9.564       21.214\n",
       "3      8.630       15.687\n",
       "4     14.669       22.803"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Perform the analysis here\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from scipy import stats\n",
    "import random\n",
    "random.seed(42)\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "df = pd.read_csv('stroopdata.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(14.051124999999999, 22.015916666666666)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Lower case of column name\n",
    "df.columns = map(str.lower, df.columns)\n",
    "\n",
    "# Find the mean\n",
    "df.congruent.mean(), df.incongruent.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(14.3565, 21.0175)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find the median\n",
    "df.congruent.median(), df.incongruent.median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(8.6300000000000008, 15.687000000000001)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find the mode\n",
    "df.congruent.mode()[0], df.incongruent.mode()[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(8.6300000000000008,\n",
       " 15.687000000000001,\n",
       " 22.328000000000003,\n",
       " 35.255000000000003)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find the min and max\n",
    "\n",
    "df.congruent.min(), df.incongruent.min(), df.congruent.max(), df.incongruent.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(12.669029070652176, 23.011757036231884)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find the variance\n",
    "df.congruent.var(), df.incongruent.var()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3.5593579576451955, 4.7970571224691376)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Find STD\n",
    "np.std(df.congruent, ddof = 1), np.std(df.incongruent, ddof = 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**_Answer_**\n",
    "\n",
    "\n",
    "Compare the central tendency of both columns, incongruent group possess relatively higher values, which are mean: 22.02, median: 21.01, mode: 15.69, variance: 23.01, STD: 4.79, as opposed to congruent group, mean: 14.05, median: 14.36, mode: 8.63, variance: 12.70, STD: 3.55.\n",
    "\n",
    "\n",
    "In addition to that, for min and max values, incongruent group present the numbers of 15.69 and 35.26, respectively, whereas congruent group suggests lower figures at 8.63 and 22.33."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(4) Provide one or two visualizations that show the distribution of the sample data. Write one or two sentences noting what we observe about the plot or plots."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fea36169438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Build the visualizations here\n",
    "fig, ax = plt.subplots(1, 1, figsize = (8, 5), dpi=1000)\n",
    "# sns.distplot(df.congruent, color = 'g'); \n",
    "# sns.distplot(df.incongruent, color = 'r');\n",
    "\n",
    "sns.distplot(df.congruent, color = 'g', label=\"Congruent\");\n",
    "sns.distplot(df.incongruent, color = 'r', label=\"Incongruent\");\n",
    "plt.legend();\n",
    "ax.set_xlabel('');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**_Answer_**\n",
    "\n",
    "\n",
    "The two groups fall into normal distribution, which is symmetric. The center of incongruent group is to the right of congruent group, and the variance of both groups looks similar."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(5)  Now, perform the statistical test and report our results. What is our confidence level or Type I error associated with our test? What is our conclusion regarding the hypotheses we set up? Did the results match up with our expectations? "
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**_Regarding what test to use_**\n",
    "\n",
    "> T-score and Z-score are ideal candidates for currnt study.\n",
    "\n",
    "\n",
    "> T-score vs. Z-score: When to use a t score? The general rule of thumb for when to use a t score is when our sample:\n",
    "\n",
    "\n",
    ">> Has a sample size below 30;<br>\n",
    "<br>\n",
    "\n",
    "\n",
    ">> Has an unknown population standard deviation;<br>\n",
    "<br>\n",
    "\n",
    "\n",
    ">> We must know the standard deviation of the population and our sample size should be above 30 in order for us to be able to use the z-score. Otherwise, use the t-score.\n",
    "\n",
    "\n",
    "> __So, I chose T_Score for current study.__\n",
    "<br>\n",
    "\n",
    "\n",
    ">> There are two types of T test, namely paried T test and paired T test. Paired T test is chosen for current study, the reason is \"Paired samples\" are when observations are made on pairs of units which are similar in some respect. Usually one treatment is applied to one member of each pair and not to the other which serves as the control. Pairing (or matching as it is sometimes called) can be done on the basis of age, sex, behaviour or any other factor that might be expected to have an effect on the response variable. The purpose of pairing is to reduce the variability in the response variable that we are measuring. The more similar the two individuals are, the more effective the pairing.\n",
    "\n",
    "\n",
    "> According to the plot above, the sample size seems on a normal distribution, and according to central limit therom, given random and independent samples of N observations each, the distribution of sample means approaches normality as the size of N increases, regardless of the shape of the population distribution. So as long as there is big enough sample, the distribution of population is supposed to be normal.\n",
    "\n",
    "\n",
    "![image.png](attachment:image.png)\n",
    "\n",
    "\n",
    "http://www.statisticshowto.com/probability-and-statistics/hypothesis-testing/t-score-vs-z-score/\n",
    "\n",
    "http://support.minitab.com/en-us/minitab/17/topic-library/basic-statistics-and-graphs/hypothesis-tests/basics/directional-and-nondirectional-hypotheses/\n",
    "\n",
    "http://support.minitab.com/en-us/minitab/17/topic-library/basic-statistics-and-graphs/hypothesis-tests/basics/what-is-a-critical-value/\n",
    "\n",
    "https://en.wikipedia.org/wiki/Student%27s_t-test#Unpaired_and_paired_two-sample_t-tests\n",
    "\n",
    "http://www2.psychology.uiowa.edu/faculty/mordkoff/GradStats/part%201/I.07%20normal.pdf\n",
    "\n",
    "http://influentialpoints.com/Training/paired_t-test-principles-properties-assumptions.htm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ttest_relResult(statistic=-8.020706944109957, pvalue=4.1030005857111781e-08)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Perform the statistical test here\n",
    "\n",
    "stats.ttest_rel(df.congruent, df.incongruent)   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**_Answer_**\n",
    "\n",
    "\n",
    "Type I error associated with current test is 0.05, I set this threshold mainly refered to most studies, and the conclusion is to reject the null hypothesis as the P value is far below the threshold.  Such result matches my reasonable expection."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(6) Optional: What is responsible for the effects observed? Can we think of an alternative or similar task that would result in a similar effect? Some research about the problem will be helpful for thinking about these two questions!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**_Answer_**\n",
    "\n",
    "\n",
    "1. The difference between words and theirs background is responsible for the effects observed;\n",
    "\n",
    "\n",
    "2. Similar task would be like, if speaking telephone while driving would increase the traffic accidents?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Conclusion\n",
    "\n",
    "\n",
    "According to the statistical analyze, we reject the Null Hypothesis, which is to say the time spent on Incongruent condition is significantly higher than that of Congruent condition. \n",
    "\n",
    "\n",
    "It makes sense, as from my own anecdotal experience incongruent words requires more time for recognition as the words displayed are color words whose names do not match the colors in which they are printed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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