IQ

Visualizing the intelligence quotient (IQ) of 100 applicants using histogram and box plots.

Importing libraries and packages

# Warnings
import warnings

# Plotting
import matplotlib.pyplot as plt

warnings.filterwarnings("ignore")
%matplotlib inline

Set paths

# Path to datasets directory
data_path = "./datasets"
# Path to assets directory (for saving results to)
assets_path = "./assets"

Loading dataset

# IQ samples
iq_scores = [
    126,
    89,
    90,
    101,
    102,
    74,
    93,
    101,
    66,
    120,
    108,
    97,
    98,
    105,
    119,
    92,
    113,
    81,
    104,
    108,
    83,
    102,
    105,
    111,
    102,
    107,
    103,
    89,
    89,
    110,
    71,
    110,
    120,
    85,
    111,
    83,
    122,
    120,
    102,
    84,
    118,
    100,
    100,
    114,
    81,
    109,
    69,
    97,
    95,
    106,
    116,
    109,
    114,
    98,
    90,
    92,
    98,
    91,
    81,
    85,
    86,
    102,
    93,
    112,
    76,
    89,
    110,
    75,
    100,
    90,
    96,
    94,
    107,
    108,
    95,
    96,
    96,
    114,
    93,
    95,
    117,
    141,
    115,
    95,
    86,
    100,
    121,
    103,
    66,
    99,
    96,
    111,
    110,
    105,
    110,
    91,
    112,
    102,
    112,
    75,
]

group_a = [
    118,
    103,
    125,
    107,
    111,
    96,
    104,
    97,
    96,
    114,
    96,
    75,
    114,
    107,
    87,
    117,
    117,
    114,
    117,
    112,
    107,
    133,
    94,
    91,
    118,
    110,
    117,
    86,
    143,
    83,
    106,
    86,
    98,
    126,
    109,
    91,
    112,
    120,
    108,
    111,
    107,
    98,
    89,
    113,
    117,
    81,
    113,
    112,
    84,
    115,
    96,
    93,
    128,
    115,
    138,
    121,
    87,
    112,
    110,
    79,
    100,
    84,
    115,
    93,
    108,
    130,
    107,
    106,
    106,
    101,
    117,
    93,
    94,
    103,
    112,
    98,
    103,
    70,
    139,
    94,
    110,
    105,
    122,
    94,
    94,
    105,
    129,
    110,
    112,
    97,
    109,
    121,
    106,
    118,
    131,
    88,
    122,
    125,
    93,
    78,
]

group_b = [
    126,
    89,
    90,
    101,
    102,
    74,
    93,
    101,
    66,
    120,
    108,
    97,
    98,
    105,
    119,
    92,
    113,
    81,
    104,
    108,
    83,
    102,
    105,
    111,
    102,
    107,
    103,
    89,
    89,
    110,
    71,
    110,
    120,
    85,
    111,
    83,
    122,
    120,
    102,
    84,
    118,
    100,
    100,
    114,
    81,
    109,
    69,
    97,
    95,
    106,
    116,
    109,
    114,
    98,
    90,
    92,
    98,
    91,
    81,
    85,
    86,
    102,
    93,
    112,
    76,
    89,
    110,
    75,
    100,
    90,
    96,
    94,
    107,
    108,
    95,
    96,
    96,
    114,
    93,
    95,
    117,
    141,
    115,
    95,
    86,
    100,
    121,
    103,
    66,
    99,
    96,
    111,
    110,
    105,
    110,
    91,
    112,
    102,
    112,
    75,
]

group_c = [
    108,
    89,
    114,
    116,
    126,
    104,
    113,
    96,
    69,
    121,
    109,
    102,
    107,
    122,
    104,
    107,
    108,
    137,
    107,
    116,
    98,
    132,
    108,
    114,
    82,
    93,
    89,
    90,
    86,
    91,
    99,
    98,
    83,
    93,
    114,
    96,
    95,
    113,
    103,
    81,
    107,
    85,
    116,
    85,
    107,
    125,
    126,
    123,
    122,
    124,
    115,
    114,
    93,
    93,
    114,
    107,
    107,
    84,
    131,
    91,
    108,
    127,
    112,
    106,
    115,
    82,
    90,
    117,
    108,
    115,
    113,
    108,
    104,
    103,
    90,
    110,
    114,
    92,
    101,
    72,
    109,
    94,
    122,
    90,
    102,
    86,
    119,
    103,
    110,
    96,
    90,
    110,
    96,
    69,
    85,
    102,
    69,
    96,
    101,
    90,
]

group_d = [
    93,
    99,
    91,
    110,
    80,
    113,
    111,
    115,
    98,
    74,
    96,
    80,
    83,
    102,
    60,
    91,
    82,
    90,
    97,
    101,
    89,
    89,
    117,
    91,
    104,
    104,
    102,
    128,
    106,
    111,
    79,
    92,
    97,
    101,
    106,
    110,
    93,
    93,
    106,
    108,
    85,
    83,
    108,
    94,
    79,
    87,
    113,
    112,
    111,
    111,
    79,
    116,
    104,
    84,
    116,
    111,
    103,
    103,
    112,
    68,
    54,
    80,
    86,
    119,
    81,
    84,
    91,
    96,
    116,
    125,
    99,
    58,
    102,
    77,
    98,
    100,
    90,
    106,
    109,
    114,
    102,
    102,
    112,
    103,
    98,
    96,
    85,
    97,
    110,
    131,
    92,
    79,
    115,
    122,
    95,
    105,
    74,
    85,
    85,
    95,
]

Visualisation

# Histogram with ten bins for the given IQ scores.
plt.figure(figsize=(6, 4), dpi=150)
# Create histogram
plt.hist(iq_scores, bins=10)
plt.axvline(x=100, color="r")
plt.axvline(x=115, color="r", linestyle="--")
plt.axvline(x=85, color="r", linestyle="--")
# Add labels and title
plt.xlabel("IQ score")
plt.ylabel("Frequency")
plt.title("IQ scores for a test group of a hundred adults")
# Show plot
plt.show()

# Box plot
plt.figure(figsize=(6, 4), dpi=150)
# Create histogram
plt.boxplot(iq_scores)
# Add labels and title
ax = plt.gca()
ax.set_xticklabels(["Test group"])
plt.ylabel("IQ score")
plt.title("IQ scores for a test group of a hundred adults")
# Show plot
plt.show()

# Box plot for each of the IQ scores of the different test groups
# a, b, c and d.
plt.figure(figsize=(6, 4), dpi=150)
# Create histogram
plt.boxplot([group_a, group_b, group_c, group_d])
# Add labels and title
ax = plt.gca()
ax.set_xticklabels(["Group A", "Group B", "Group C", "Group D"])
plt.ylabel("IQ score")
plt.title("IQ scores for different test groups")
# Show plot
plt.show()