<jupyter_start><jupyter_text>Statistics: The Science of Decisions Project Instructions  Background InformationIn a Stroop task, participants are presented with a list of words, with each word displayed in a color of ink. The participant’s task is to say out loud the color of the ink in which the word is printed. The task has two conditions: a congruent words condition, and an incongruent words condition. In the congruent words condition, the words being displayed are color words whose names match the colors in which they are printed: for example RED, BLUE. In the incongruent words condition, the words displayed are color words whose names do not match the colors in which they are printed: for example PURPLE, ORANGE. In each case, we measure the time it takes to name the ink colors in equally-sized lists. Each participant will go through and record a time from each condition.  Questions For Investigation  1. What is our independent variable? What is our dependent variable? Independent variable: Word congruence (whether color of the word matches the definition of the word)Dependent variable: Time taken to name the ink colors of the words  2. What is an appropriate set of hypotheses for,  this task? What kind of statistical test do you expect to perform? Justify your choices. Null Hypothesis, H0 - Congruence of the word has no effect on the mean population time taken to name the ink colors of the wordsAlternative Hypothesis, H1 - Words where their definition not congruent with its ink color will increase the mean population time taken to name of the ink colors of the wordsH0: μ = μ0 (same mean population time)H1: μ > μ0 (a upper-tailed test) (mean populataion time for incongruent words are longer than congruent words)A one-tail paired t-test will be carried out to study whether there are significant difference in time taken to identify the ink colors of the words due to congruence. A t-test is used instead of a Z-test as the population parameters are unknown.An alpha, α = 0.05 is used as a threshold whether to reject or accept the null hypothesis.  3. Report some descriptive statistics regarding this dataset. Include at least one measure of central tendency and at least one measure of variability.<jupyter_code>'''Importing all required libraries'''
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
stroop = pd.read_csv("stroopdata.csv")
stroop['Mean Difference'] = stroop['Incongruent'] - stroop['Congruent'] #A new column for population is created by adding up female and male pop.
print(stroop)
stroop.describe()
stroop.median()<jupyter_output><empty_output><jupyter_text>Median is chosen as the measure of central tendency.Standard deviation is chosen as the measure of variability.  4. Provide one or two visualizations that show the distribution of the sample data. Write one or two sentences noting what you observe about the plot or plots.<jupyter_code>stroop.hist()<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.04226769540422677, 'fraction_numerical': 0.004360952700436095, 'mean_word_length': 4.964, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 10, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '191003', 'license': 'MIT', 'n_tokens_mistral': 754, 'n_tokens_neox': 712, 'n_words': 447, 'path': 'Stroop-Effect.ipynb', 'repo_name': 'blockchainhelppro/dataanalysis-Crypto', 'size': '2981'}