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Scientific-Method-Final-Project

import pandas as pd import numpy as np import matplotlib.pyplot as plt import statistics

#SCATTER PLOT

df = pd.read_csv("Class Data 2 - Sheet1.csv") sleep = df["Avg night sleep(hrs)"] words = df["Words Recalled"] words = words.dropna() sleep = sleep.dropna()

np.mean(sleep) np.mean(words) plt.clf()

plt.scatter(sleep, words, s=50, color = 'blue', alpha = 0.7) fit = np.polyfit(sleep, words, 1) plt.plot(sleep, fit[0] * sleep + fit[1], color = 'red') plt.xlabel("Hours of Sleep") plt.ylabel("Numbers of Words") plt.title("One Week Data") plt.show()

#T-TEST

df = pd.read_csv("Class Data - Sheet1.csv") def tvalue(groupA,groupB): XA=np.mean(groupA) XB=np.mean(groupB) SA=statistics.stdev(groupA) SB=statistics.stdev(groupB) nA=len(groupA) nB=len(groupB) tvalue = (abs(np.mean(one) - np.mean(two))) / (np.sqrt(((np.var(one))/len(one)) + ((np.var(two))/len(two)))) df = pd.read_csv("Class Data - Sheet1.csv") data2=df["Words recalled"].loc[df["Avg night sleep(hrs)"]>=7] data1=df["Words recalled"].loc[df["Avg night sleep(hrs)"]<7] def tvalue(groupA,groupB): XA=np.mean(groupA) XB=np.mean(groupB) SA=np.std(groupA) SB=np.std(groupB) nA=len(groupA) nB=len(groupB) tvalue=(abs(XA-XB))/(np.sqrt((SA2/nA)+(SB2/nB))) return(tvalue) print(tvalue(data1,data2))

#HISTOGRAM

df.head(12) plt.clf() plt.hist (os) plt.axvline (7, linestyle = "dashed", color = "skyblue") plt.xlabel ("Avg night sleep (hrs)") plt.ylabel ("Student") plt.suptitle ("Frequncy of Hours of Sleep 2") plt.show()

#BAR GRAPH

plt.clf() plt.bar(0, np.mean(sleep7), yerr = np.std(sleep7), capsize = 5, color = 'purple') plt.bar(1, np.mean(sleep6), yerr = np.std(sleep6), capsize = 5, color = 'b') plt.xticks([0,1], ["7+ hours of sleep", "Under 7 hours of sleep"]) plt.ylabel("Number of Words Correct") plt.show()

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