ꯔꯨꯂꯦꯠꯀꯤ ꯃꯦꯊꯃꯦꯇꯤꯛꯁ · ꯋꯥꯈꯜꯂꯣꯟ · ꯃꯤꯅꯤꯠ 10

ꯖꯨꯌꯥ ꯁꯥꯟꯅꯔꯤꯕꯒꯤ ꯑꯔꯥꯟꯕ ꯋꯥꯈꯜ

ꯃꯍꯩ ꯑꯃꯥ ꯃꯇꯝ ꯈꯔꯥ ꯊꯣꯛꯇꯔꯕꯅ “ꯍꯧꯖꯤꯛ ꯊꯣꯛꯀꯗꯕꯅꯤ” ꯍꯥꯌꯅ ꯊꯥꯖꯕ꯫

ꯊꯨꯅ ꯄꯥꯎꯈꯨꯝ

ꯑꯉꯥꯡꯕ ꯇꯔꯥꯒꯤ ꯃꯇꯨꯡꯗꯁꯨ ꯑꯃꯨꯕꯒꯤ ꯊꯣꯛꯄꯒꯤ ꯈꯨꯗꯣꯡꯆꯥꯕ 18/37 ꯅꯤ꯫ ꯆꯛꯔꯅ ꯀꯔꯤꯁꯨ ꯅꯤꯡꯁꯤꯡꯗꯦ ꯑꯃꯁꯨꯡ ꯀꯅꯥꯒꯨꯝꯕ ꯑꯃꯒꯤꯁꯨ ꯁꯦꯜ ꯄꯤꯒꯗꯕ ꯂꯩꯇꯦ꯫

p(ꯑꯉꯥꯡꯕ 10 ꯒꯤ ꯃꯇꯨꯡꯗ ꯑꯃꯨꯕ)

48.65%

p(ꯑꯉꯥꯡꯕ 0 ꯒꯤ ꯃꯇꯨꯡꯗ ꯑꯃꯨꯕ)

48.65%

ꯃꯣꯟꯇꯦ ꯀꯥꯔꯂꯣ, 1913

ꯑꯃꯨꯕ 26

ꯑꯇꯣꯞꯄ ꯃꯃꯤꯡ

ꯃꯣꯟꯇꯦ ꯀꯥꯔꯂꯣꯒꯤ ꯑꯔꯥꯟꯕ ꯋꯥꯈꯜ

ꯑꯔꯥꯟꯕ ꯋꯥꯈꯜ

ꯑꯉꯥꯡꯕꯕꯦꯠꯑꯉꯥꯡꯕꯑꯉꯥꯡꯕ ꯃꯁꯤꯡ 18 ꯗ ꯊꯝꯕ ꯆꯞ ꯃꯥꯟꯅꯕ ꯕꯦꯠ꯫ ꯐ꯭ꯔꯦꯟꯆ: ꯔꯨꯖ꯫ꯃꯄꯨꯡ ꯄꯥꯕꯤꯌꯨ → ꯑꯃꯨꯛ ꯇꯔꯥ ꯊꯣꯀꯂꯕꯗ ꯁꯥꯟꯅꯔꯤꯕ ꯀꯌꯥꯅ ꯑꯃꯨꯕꯕꯦꯠꯑꯃꯨꯕꯑꯃꯨꯕ ꯃꯁꯤꯡ 18 ꯗ ꯊꯝꯕ ꯆꯞ ꯃꯥꯟꯅꯕ ꯕꯦꯠ꯫ ꯐ꯭ꯔꯦꯟꯆ: ꯅꯣꯌꯥꯔ꯫ꯃꯄꯨꯡ ꯄꯥꯕꯤꯌꯨ → “ꯍꯧꯖꯤꯛ ꯊꯣꯛꯀꯗꯕꯅꯤ” ꯍꯥꯌꯅ ꯐꯥꯑꯣꯏ ꯑꯃꯁꯨꯡ ꯃꯗꯨꯒꯤ ꯃꯇꯨꯡ ꯏꯟꯅꯥ ꯕꯦꯠ ꯊꯝꯃꯤ꯫ ꯑꯇꯣꯞꯄꯁꯤꯡꯅ ꯑꯉꯥꯡꯕ “ꯁꯥꯠꯂꯤ” ꯍꯥꯌꯅ ꯐꯥꯑꯣꯏ ꯑꯃꯁꯨꯡ ꯃꯗꯨꯗ ꯕꯦꯠ ꯊꯝꯃꯤ꯫ ꯑꯅꯤꯃꯛꯅ ꯂꯣꯏꯔꯕ ꯃꯊꯪ ꯃꯊꯪ ꯑꯃꯗꯒꯤ ꯍꯧꯖꯤꯛ ꯐꯥꯑꯣꯕ ꯊꯣꯛꯇꯕ ꯁ꯭ꯄꯤꯟ ꯑꯃꯒꯤ ꯃꯇꯥꯡꯗ ꯋꯥꯈꯜ ꯈꯟꯂꯤ꯫ ꯕꯣꯜꯈꯨꯠꯂꯥꯏꯕꯣꯜꯔꯣꯇꯔꯒꯤ ꯃꯥꯌꯣꯛꯇ ꯇ꯭ꯔꯦꯛꯇ ꯊꯥꯗꯣꯛꯄ ꯑꯄꯤꯛꯄ ꯕꯣꯜ꯫ ꯍꯧꯖꯤꯛꯀꯤ ꯕꯣꯜꯁꯤꯡ ꯑꯥꯏꯚꯣꯔꯤꯟ ꯅꯠꯔꯒ ꯇꯦꯐ꯭ꯂꯣꯅꯅ ꯁꯦꯝꯃꯤ, 18–21 mm꯫ꯃꯄꯨꯡ ꯄꯥꯕꯤꯌꯨ → ꯑꯗꯨꯅ ꯑꯔꯣꯏꯕ ꯁ꯭ꯄꯤꯟ ꯇꯔꯥ ꯀꯔꯤ ꯑꯣꯏꯈꯤꯕꯒꯦ ꯈꯉꯗꯦ; ꯄꯣꯀꯦꯠꯁꯤꯡꯈꯨꯠꯂꯥꯏꯄꯣꯀꯦꯠꯔꯣꯇꯔꯗ ꯂꯩꯕ ꯃꯁꯤꯡ ꯏꯔꯕ ꯀꯣꯠ 37 ꯒꯤ ꯃꯅꯨꯡꯗ ꯑꯃꯥ꯫ ꯑꯇꯣꯞꯄ ꯃꯃꯤꯡ: ꯁ꯭ꯂꯣꯠ, ꯀꯞ꯫ꯃꯄꯨꯡ ꯄꯥꯕꯤꯌꯨ → ꯄꯨꯡ ꯑꯃꯒꯤ ꯃꯃꯥꯡꯗ ꯂꯩꯔꯝꯕ ꯆꯥꯎꯕ ꯑꯗꯨꯃꯛꯇꯅꯤ; ꯑꯃꯨꯕꯒꯤ ꯊꯣꯛꯄꯒꯤ ꯈꯨꯗꯣꯡꯆꯥꯕꯃꯦꯊꯃꯦꯇꯤꯛꯁꯊꯣꯛꯄꯒꯤ ꯈꯨꯗꯣꯡꯆꯥꯕꯃꯍꯩ ꯑꯃꯥ ꯊꯣꯛꯄꯒꯤ ꯈꯨꯗꯣꯡꯆꯥꯕ, 0 ꯗꯒꯤ 1 ꯐꯥꯑꯣꯕ ꯅꯠꯔꯒ 0% ꯗꯒꯤ 100% ꯐꯥꯑꯣꯕ꯫ ꯃꯁꯤꯡ ꯑꯃꯥ: 1/37 = 2.70%꯫ꯃꯄꯨꯡ ꯄꯥꯕꯤꯌꯨ → ꯃꯇꯝ ꯄꯨꯝꯅꯃꯛꯇ ꯂꯩꯔꯝꯕꯒꯨꯝꯅ 18/37 ꯅꯤ꯫

ꯑꯔꯥꯟꯕ ꯊꯥꯖꯕ: ꯃꯁꯤꯡꯁꯤꯡ ꯊꯣꯛꯀꯗꯕ ꯃꯇꯝ ꯂꯥꯛꯂꯦ

ꯀꯔꯤꯒꯤ ꯑꯆꯨꯝꯕꯒꯨꯝ ꯐꯥꯑꯣꯕꯒꯦ

ꯃꯇꯝ ꯁꯥꯡꯅ ꯑꯉꯥꯡꯕ ꯑꯃꯁꯨꯡ ꯑꯃꯨꯕꯒꯤ ꯆꯥꯡ ꯑꯃꯃꯃꯅ 18/37 ꯗ ꯇꯁꯦꯡꯅ ꯅꯛꯂꯛꯏ꯫ ꯑꯆꯧꯕ ꯃꯁꯤꯡꯒꯤ ꯅꯤꯌꯝꯅꯃꯦꯊꯃꯦꯇꯤꯛꯁꯑꯆꯧꯕ ꯃꯁꯤꯡꯒꯤ ꯅꯤꯌꯝꯍꯣꯠꯅꯕꯒꯤ ꯃꯁꯤꯡ ꯍꯦꯅꯒꯠꯂꯀꯄꯒ ꯂꯣꯌꯅꯅ ꯃꯔꯤ ꯂꯩꯅꯗꯕ ꯃꯍꯩꯁꯤꯡꯒꯤ ꯑꯦꯚꯔꯦꯖ ꯑꯗꯨ ꯐꯪꯒꯗꯕ ꯃꯃꯂꯗ ꯅꯛꯂꯛꯏ꯫ꯃꯄꯨꯡ ꯄꯥꯕꯤꯌꯨ → ꯃꯁꯤ ꯁꯣꯏꯗꯅ ꯑꯣꯏꯍꯜꯂꯤ꯫ ꯑꯗꯨꯕꯨ ꯅꯛꯂꯛꯄ ꯑꯁꯤ ꯌꯥꯎꯊꯣꯀꯄꯅ ꯊꯣꯀꯏ, ꯆꯨꯃꯊꯣꯀꯄꯅ ꯊꯣꯀꯄ ꯅꯠꯇꯦ: ꯍꯦꯟꯅꯥ ꯁ꯭ꯄꯤꯟ 1,000 ꯒꯤ ꯃꯇꯨꯡꯗ ꯍꯦꯟꯅꯥ ꯊꯣꯀꯈꯤꯕ ꯑꯉꯥꯡꯕ ꯇꯔꯥ ꯑꯗꯨ ꯆꯥꯡꯗ ꯌꯦꯡꯁꯤꯟꯕ ꯌꯥꯗꯕ ꯑꯄꯤꯀꯄ ꯑꯔꯥꯟꯕ ꯑꯃꯈꯛ ꯑꯣꯏꯔꯛꯏ, ꯑꯃꯨꯕꯅ ꯃꯇꯨꯡ ꯇꯥꯔꯛꯂꯕꯅ ꯅꯠꯇꯦ, ꯁꯦꯝꯄꯜ ꯑꯗꯨ ꯆꯥꯎꯔꯛꯂꯕꯅꯤ꯫ ꯑꯃꯨꯕ ꯍꯦꯟꯅꯥ ꯊꯣꯛꯄ ꯌꯥꯍꯟꯕ ꯃꯑꯣꯡ ꯑꯃꯠꯇ ꯂꯩꯇꯦ, ꯑꯃꯁꯨꯡ ꯑꯆꯧꯕ ꯃꯁꯤꯡꯒꯤ ꯅꯤꯌꯝꯅ ꯃꯁꯤꯒꯨꯝꯕ ꯑꯃꯥ ꯃꯊꯧ ꯇꯥꯗꯦ꯫

ꯑꯉꯥꯡꯕ 10 ꯒꯤ ꯃꯇꯨꯡꯗ, ꯃꯗꯨꯒꯤ ꯃꯇꯨꯡꯗ ꯆꯨꯝꯃꯤꯟꯅꯕ ꯁ꯭ꯄꯤꯟ Nꯐꯪꯒꯗꯕ ꯑꯉꯥꯡꯕꯐꯪꯒꯗꯕ ꯑꯃꯨꯕꯑꯉꯥꯡꯕꯒꯤ ꯆꯥꯡ

N = 0100100%

N = 100≈ 58.6≈ 48.6≈ 55%

N = 1,000≈ 496≈ 486≈ 50.5%

N = 100,000≈ 48,660≈ 48,650≈ 50.005%

ꯍꯦꯟꯅꯥ ꯊꯣꯀꯈꯤꯕ ꯑꯉꯥꯡꯕ ꯇꯔꯥ ꯑꯗꯨ ꯀꯩꯗꯧꯉꯩꯗꯁꯨ ꯃꯥꯡꯗꯦ꯫ ꯃꯁꯤ ꯃꯔꯨ ꯑꯣꯏꯗꯕ ꯑꯣꯏꯔꯛꯏ꯫

ꯃꯣꯟꯇꯦ ꯀꯥꯔꯂꯣ, 1913 ꯒꯤ ꯑꯒꯁ꯭ꯠ 18

ꯀꯥꯁꯤꯅꯣ ꯗꯦ ꯃꯣꯟꯇꯦ-ꯀꯥꯔꯂꯣꯒꯤ ꯇꯦꯕꯜ ꯑꯃꯗ ꯃꯈꯥ ꯆꯠꯅꯅ ꯑꯃꯨꯕ ꯑꯃꯨꯛ 26 ꯊꯣꯀꯈꯤ꯫ ꯑꯃꯨꯕ ꯇꯔꯥꯃꯉꯥꯁꯨꯕ ꯃꯔꯛꯇꯒꯤ ꯁꯥꯟꯅꯔꯤꯕꯁꯤꯡꯅ ꯑꯉꯥꯡꯕꯗ ꯌꯥꯝꯅꯥ ꯊꯝꯈꯤ, ꯑꯅꯤ ꯊꯥꯛ ꯑꯃꯁꯨꯡ ꯑꯃꯨꯛ ꯍꯟꯅꯥ ꯑꯅꯤ ꯊꯥꯛ ꯍꯦꯅꯒꯠꯍꯟꯗꯨꯅ, ꯁ꯭ꯄꯤꯟ ꯈꯨꯗꯤꯡꯃꯛ ꯃꯃꯥꯡꯒꯤꯗꯒꯤ “ꯍꯦꯟꯅꯥ ꯁꯣꯏꯗꯅ” ꯐꯥꯑꯣꯈꯤ꯫ ꯀꯦꯁꯤꯅꯣꯅ ꯐ꯭ꯔꯥꯉ꯭ꯛ ꯂꯤꯁꯤꯡ ꯀꯌꯥ ꯃꯥꯏꯄꯥꯀꯈꯤ꯫ ꯑꯍꯥꯅꯕ ꯑꯃꯨꯕꯗꯒꯤ ꯁ꯭ꯇ꯭ꯔꯤꯛ ꯑꯗꯨꯒꯤ ꯈꯨꯗꯣꯡꯆꯥꯕ 137 ꯃꯤꯂꯤꯌꯟꯗꯒꯤ 1 ꯅꯤ, ꯑꯃꯁꯨꯡ ꯃꯥꯂꯦꯃꯒꯤ ꯀꯦꯁꯤꯅꯣꯁꯤꯡꯒꯤ ꯀꯗꯥꯏꯗꯥ ꯑꯃꯗ ꯃꯁꯤ ꯑꯔꯣꯏꯕꯗ ꯊꯣꯛꯀꯗꯕꯒꯤ ꯈꯨꯗꯣꯡꯆꯥꯕꯗꯤ ꯌꯥꯝꯅꯥ ꯅꯛꯅꯥ ꯑꯃꯅꯤ꯫ ꯃꯔꯝ ꯑꯁꯤꯅ ꯖꯨꯌꯥ ꯁꯥꯟꯅꯔꯤꯕꯒꯤ ꯑꯔꯥꯟꯕ ꯋꯥꯈꯜ ꯑꯁꯤꯕꯨ ꯃꯣꯟꯇꯦ ꯀꯥꯔꯂꯣꯒꯤ ꯑꯔꯥꯟꯕ ꯋꯥꯈꯜ ꯍꯥꯌꯅꯁꯨ ꯀꯧꯏ꯫

1913 ꯒꯤ ꯁ꯭ꯇ꯭ꯔꯤꯛ, ꯑꯔꯥꯟꯕ ꯋꯥꯈꯂꯅ ꯎꯈꯤꯕ ꯃꯑꯣꯡꯗ

ꯑꯃꯨꯕ × 5

ꯑꯉꯀꯄ ꯅꯠꯇꯦ꯫ ꯃꯇꯝ 44 ꯗ ꯑꯃꯨꯛ ꯊꯣꯀꯏ꯫

ꯑꯃꯨꯕ × 10

ꯁꯥꯟꯅꯔꯤꯕꯁꯤꯡꯅ ꯈꯉꯂꯛꯂꯤ꯫ ꯑꯉꯥꯡꯕ “ꯍꯧꯖꯤꯛ ꯊꯣꯛꯀꯗꯕꯅꯤ”꯫

ꯑꯃꯨꯕ × 15

ꯇꯦꯕꯜ ꯑꯗꯨ ꯃꯤꯅ ꯊꯟꯊꯔꯦ꯫ ꯃꯥꯏꯊꯤꯕ ꯈꯨꯗꯤꯡꯒꯤ ꯃꯇꯨꯡꯗ ꯑꯉꯥꯡꯕꯗ ꯊꯝꯂꯕ ꯁꯦꯜ ꯑꯅꯤ ꯊꯥꯛ ꯍꯦꯅꯒꯠꯍꯜꯂꯤ꯫

ꯑꯃꯨꯕ × 20

ꯂꯟ-ꯊꯨꯝ ꯌꯥꯝꯅꯥ ꯃꯥꯡꯈꯤ꯫ ꯑꯅꯧꯕ ꯑꯃꯨꯕ ꯈꯨꯗꯤꯡꯅ ꯑꯉꯥꯡꯕ ꯍꯦꯟꯅꯥ ꯁꯣꯏꯗꯅ ꯐꯥꯑꯣꯍꯜꯂꯤ꯫

ꯑꯃꯨꯕ × 26

ꯁ꯭ꯇ꯭ꯔꯤꯛ ꯑꯗꯨ ꯂꯣꯏꯔꯦ꯫ ꯃꯁꯥꯅ ꯁ꯭ꯇ꯭ꯔꯤꯛ ꯑꯃꯅꯤ ꯍꯥꯌꯕ “ꯈꯉꯕ” ꯉꯃꯗꯕ ꯁ꯭ꯇ꯭ꯔꯤꯛ ꯑꯃꯒꯤ ꯃꯥꯌꯣꯛꯇ ꯕꯦꯠ ꯊꯝꯂꯤꯕ ꯃꯤꯁꯤꯡꯗꯒꯤ ꯀꯦꯁꯤꯅꯣꯅ ꯐ꯭ꯔꯥꯉ꯭ꯛ ꯂꯤꯁꯤꯡ ꯀꯌꯥ ꯃꯥꯏꯄꯥꯀꯈ꯭ꯔꯦ꯫

ꯀꯦꯁꯤꯅꯣ ꯗꯤ ꯃꯣꯟꯇꯦ-ꯀꯥꯔꯂꯣ

ꯍꯣꯠ ꯍꯦꯟꯗ

ꯃꯆꯨ ꯑꯃꯥ ꯁ꯭ꯇ꯭ꯔꯤꯛꯇ ꯂꯩꯔꯤꯕꯅ ꯃꯗꯨꯗ ꯕꯦꯠ ꯊꯝꯕ ꯑꯁꯤ ꯑꯔꯥꯟꯕ ꯑꯗꯨꯃꯛ ꯑꯣꯟꯊꯣꯛꯂꯕꯅꯤ: ꯁ꯭ꯇ꯭ꯔꯤꯛ ꯑꯗꯨ ꯂꯣꯏꯒꯅꯤ ꯍꯥꯌꯅ ꯅꯠꯇꯅ ꯃꯈꯥ ꯆꯠꯊꯒꯅꯤ ꯍꯥꯌꯅ ꯊꯥꯖꯩ꯫ ꯁꯥꯏꯀꯣꯂꯣꯖꯤꯁ꯭ꯇꯁꯤꯡꯅ ꯃꯁꯤꯕꯨ ꯍꯣꯠ ꯍꯦꯟꯗꯑꯔꯥꯟꯕ ꯊꯥꯖꯕꯍꯣꯠ ꯍꯦꯟꯗꯃꯥꯏꯄꯥꯛꯄꯒꯤ ꯁ꯭ꯇ꯭ꯔꯤꯛ, ꯅꯠꯔꯒ ꯃꯍꯩ ꯑꯃꯒꯤ ꯁ꯭ꯇ꯭ꯔꯤꯛ ꯑꯃꯅ ꯑꯇꯣꯞꯄ ꯑꯃꯥ ꯊꯣꯛꯅꯕ ꯍꯦꯟꯅꯥ ꯌꯥꯍꯜꯂꯤ ꯍꯥꯌꯅ ꯊꯥꯖꯕ꯫ ꯆꯛꯔꯗ ꯃꯁꯤ ꯖꯨꯌꯥ ꯁꯥꯟꯅꯔꯤꯕꯒꯤ ꯑꯔꯥꯟꯕ ꯋꯥꯈꯜ ꯑꯗꯨ ꯑꯣꯟꯊꯣꯛꯂꯕꯅꯤ꯫ꯃꯄꯨꯡ ꯄꯥꯕꯤꯌꯨ → ꯍꯥꯌꯅ ꯀꯧꯏ, ꯒꯤꯂꯣꯚꯤꯆ, ꯚꯦꯂꯣꯟ ꯑꯃꯁꯨꯡ ꯇꯚꯔꯁ꯭ꯀꯤꯅ 1985 ꯗ ꯕꯥꯁ꯭ꯀꯦꯠꯕꯣꯂꯗ ꯕꯣꯜ ꯊꯥꯗꯣꯀꯄꯗ ꯁ꯭ꯇ꯭ꯔꯤꯛ ꯊꯤꯈꯤꯕ ꯑꯃꯁꯨꯡ ꯂꯥꯛꯀꯤ ꯃꯊꯛꯇ ꯑꯃꯠꯇ ꯐꯪꯗꯈꯤꯕ ꯊꯤꯖꯤꯟꯕ ꯑꯃꯒꯤ ꯃꯇꯨꯡ ꯏꯟꯅꯥ꯫ 2018 ꯗ ꯃꯤꯂꯔ ꯑꯃꯁꯨꯡ ꯁꯥꯟꯖꯨꯔꯖꯣꯅ ꯇꯦꯁ꯭ꯠ ꯑꯗꯨ ꯃꯁꯥꯃꯛ ꯌꯦꯟꯊꯔꯝꯃꯤ ꯍꯥꯌꯅ ꯎꯠꯈꯤ: ꯃꯇꯝ ꯀꯨꯞꯄ ꯔꯦꯀꯣꯔꯗ ꯑꯃꯗ ꯊꯣꯀꯄꯥ ꯃꯇꯨꯡꯗ ꯍꯧꯖꯤꯛꯇꯒꯤ ꯊꯣꯀꯄꯒꯤ ꯆꯥꯡ ꯑꯗꯨ ꯑꯦꯚꯔꯦꯖꯗ ꯊꯥꯗꯣꯀꯄ ꯃꯤ ꯑꯗꯨꯒꯤ ꯄꯨꯝꯅꯃꯛꯀꯤ ꯆꯥꯡꯗꯒꯤ ꯅꯦꯝꯅ ꯂꯥꯀꯏ, ꯃꯔꯝ ꯑꯗꯨꯅ ꯍꯣꯠ ꯍꯦꯟꯗ ꯑꯃꯠꯇ ꯂꯩꯇꯕ ꯁꯥꯟꯅꯔꯤꯕ ꯑꯃꯥ ꯈꯔꯥ ꯏꯪꯕꯒꯨꯝ ꯎꯏ꯫ ꯆꯨꯃꯊꯣꯛꯂꯕꯗ ꯗꯦꯇꯥ ꯑꯗꯨꯃꯛꯅ ꯑꯄꯤꯀꯄ ꯍꯣꯠ ꯍꯦꯟꯗ ꯑꯃꯥ ꯎꯠꯂꯤ꯫ ꯃꯤꯑꯣꯏ ꯑꯃꯥ ꯁꯥꯠꯂꯛꯄ ꯌꯥꯏ; ꯆꯛꯔ ꯑꯃꯒꯤ ꯂꯩꯒꯗꯕ ꯐꯤꯚꯝ ꯑꯃꯠꯇ ꯂꯩꯇꯦ꯫ ꯁꯥꯟꯅꯔꯤꯕ ꯈꯔꯅ ꯊꯥꯖꯕ ꯑꯅꯤꯃꯛ ꯃꯇꯝ ꯑꯃꯗ ꯊꯝꯃꯤ, ꯁ꯭ꯇ꯭ꯔꯤꯛ ꯑꯃꯥ “ꯌꯥꯝꯅꯥ ꯁꯥꯡꯂꯛꯠꯔꯤꯉꯩ” ꯐꯥꯑꯣꯕ ꯃꯈꯥ ꯆꯠꯊꯒꯅꯤ ꯑꯃꯁꯨꯡ ꯃꯗꯨꯒꯤ ꯃꯇꯨꯡꯗ ꯂꯣꯏꯒꯅꯤ꯫ ꯆꯨꯝꯃꯤꯟꯅꯕ ꯆꯛꯔ ꯑꯃꯗ ꯃꯈꯜ ꯈꯨꯗꯤꯡꯃꯛꯀꯤ ꯐꯪꯒꯗꯕ ꯃꯃꯜꯃꯦꯊꯃꯦꯇꯤꯛꯁꯐꯪꯒꯗꯕ ꯃꯃꯜꯃꯇꯝ ꯁꯥꯡꯅ ꯌꯦꯡꯂꯕꯗ ꯕꯦꯠ ꯑꯃꯒꯤ ꯑꯦꯚꯔꯦꯖ ꯃꯍꯩ꯫ ꯃꯔꯨꯑꯣꯏꯕ ꯌꯨꯔꯣꯄꯤꯌꯟ ꯕꯦꯠ ꯈꯨꯗꯤꯡꯗ ꯊꯝꯂꯕ ꯁꯦꯜꯒꯤ −1/37꯫ꯃꯄꯨꯡ ꯄꯥꯕꯤꯌꯨ → ꯀꯣꯏꯟ ꯊꯥꯗꯨꯅ ꯃꯆꯨ ꯈꯅꯕꯒꯥ ꯃꯥꯟꯅꯩ: ꯊꯝꯂꯕ ꯁꯦꯜꯒꯤ −2.70%꯫

ꯔꯨꯂꯦꯠꯇ ꯁ꯭ꯇ꯭ꯔꯤꯛ ꯊꯣꯛꯄꯒꯤ ꯈꯨꯗꯣꯡꯆꯥꯕ

ꯑꯁꯦꯡꯕ ꯇꯦꯕꯜ ꯑꯃꯗ

ꯀ꯭ꯔꯣꯁꯟ ꯑꯃꯁꯨꯡ ꯁꯨꯟꯗꯥꯂꯤ (2005) ꯅ ꯔꯤꯅꯣꯒꯤ ꯑꯆꯧꯕ ꯀꯦꯁꯤꯅꯣ ꯑꯃꯒꯤ ꯗꯕꯜ-ꯖꯤꯔꯣꯆꯛꯔꯖꯤꯔꯣꯆꯞ ꯃꯥꯟꯅꯕ, ꯗꯖꯟ ꯅꯠꯔꯒ ꯀꯂꯝ ꯕꯦꯠ ꯑꯃꯠꯇꯅ ꯀꯨꯞꯇꯕ ꯑꯁꯪꯕ ꯄꯣꯀꯦꯠ ꯑꯃꯈꯛꯇ; ꯍꯥꯎꯁ ꯑꯦꯖꯀꯤ ꯍꯧꯔꯀꯐꯝꯅꯤ꯫ ꯑꯇꯣꯞꯄ ꯃꯃꯤꯡ: ꯁꯤꯡꯒꯜ ꯖꯤꯔꯣ, 0꯫ꯃꯄꯨꯡ ꯄꯥꯕꯤꯌꯨ → ꯇꯦꯕꯜ ꯑꯃꯒꯤ ꯁꯦꯛꯌꯨꯔꯤꯇꯤ ꯚꯤꯗꯤꯑꯣ ꯄꯨꯡ 18 ꯌꯦꯡꯈꯤ: ꯁꯥꯟꯅꯔꯤꯕ 139 ꯅ ꯕꯦꯠ 24,131 ꯊꯝꯈꯤ꯫ ꯆꯞ ꯃꯥꯟꯅꯕ ꯕꯦꯠꯁꯤꯡꯕꯦꯠꯆꯞ ꯃꯥꯟꯅꯕ ꯕꯦꯠꯑꯉꯥꯡꯕ/ꯑꯃꯨꯕ, ꯕꯤꯖꯣꯔ/ꯖꯣꯔ, ꯑꯋꯥꯡꯕ/ꯑꯅꯦꯝꯕ꯫ ꯃꯁꯤꯡ 18, 1:1 ꯄꯦꯑꯥꯎꯠ꯫ꯃꯄꯨꯡ ꯄꯥꯕꯤꯌꯨ →ꯗ ꯁꯥꯟꯅꯔꯤꯕꯁꯤꯡ ꯀꯨꯞꯄ ꯁ꯭ꯇ꯭ꯔꯤꯛ ꯃꯇꯨꯡ ꯏꯟꯕ ꯑꯃꯁꯨꯡ ꯃꯥꯌꯣꯛꯅꯕꯗ ꯑꯌꯥꯝꯕꯅ ꯆꯞ ꯃꯥꯟꯅꯅ ꯈꯥꯌꯗꯣꯀꯈꯤ꯫ ꯃꯈꯥ ꯆꯠꯅꯅ ꯃꯑꯣꯡ ꯑꯃꯒꯤ ꯃꯉꯥꯒꯤ ꯃꯇꯨꯡꯗ ꯃꯈꯣꯌꯅ ꯁ꯭ꯇ꯭ꯔꯤꯛꯀꯤ ꯃꯥꯌꯣꯛꯇ ꯊꯝꯂꯛꯈꯤ, ꯑꯃꯁꯨꯡ ꯇꯔꯨꯛ ꯅꯠꯔꯒ ꯍꯦꯟꯕꯒꯤ ꯃꯇꯨꯡꯗ ꯃꯈꯣꯌꯒꯤ ꯕꯦꯠꯁꯤꯡꯒꯤ 85% ꯑꯇꯣꯞꯄ ꯃꯥꯏꯀꯩꯗ ꯂꯩꯈꯤ꯫ ꯁꯥꯟꯅꯔꯤꯕ ꯑꯗꯨꯃꯛꯅ ꯃꯁꯥꯒꯤ ꯃꯇꯥꯡꯗ ꯍꯣꯠ ꯍꯦꯟꯗ ꯊꯥꯖꯈꯤ: ꯃꯁꯤꯡꯁꯤꯡꯗ ꯃꯥꯏꯄꯥꯛꯂꯕꯥ ꯃꯇꯨꯡꯗ ꯃꯈꯣꯌꯅ ꯃꯊꯪꯒꯤ ꯁ꯭ꯄꯤꯟꯗ ꯑꯦꯚꯔꯦꯖꯗ ꯃꯁꯤꯡ 13.6 ꯀꯨꯞꯈꯤ, ꯃꯥꯏꯊꯤꯔꯕꯥ ꯃꯇꯨꯡꯗ 9.2 ꯈꯛꯇꯅꯤ꯫ ꯃꯈꯣꯌꯒꯤ ꯆꯛꯔꯗ ꯕꯥꯏꯌꯥꯁꯀꯤ ꯈꯨꯗꯝ ꯑꯃꯠꯇ ꯎꯈꯤꯗꯦ, ꯃꯔꯝ ꯑꯗꯨꯅ ꯃꯁꯤꯒꯤ ꯀꯔꯤꯒꯨꯝꯕ ꯑꯃꯠꯇꯅ ꯃꯈꯣꯌꯅ ꯐꯪꯒꯗꯕ ꯑꯗꯨ ꯍꯣꯡꯍꯟꯈꯤꯗꯦ꯫

ꯀꯦꯁꯤꯅꯣꯒꯤ ꯃꯄꯥꯟꯗ

ꯑꯁꯦꯡꯕ ꯋꯥꯔꯦꯞ ꯂꯧꯕ ꯃꯐꯃꯁꯤꯡꯗꯁꯨ ꯂꯧꯁꯤꯡ ꯑꯁꯤꯃꯛ ꯎꯏ꯫ ꯀ꯭ꯂꯣꯠꯐꯦꯜꯇꯔ ꯑꯃꯁꯨꯡ ꯀꯨꯛ (1993) ꯅ ꯃꯦꯔꯤꯂꯦꯟꯗꯀꯤ ꯅꯨꯃꯤꯠ ꯈꯨꯗꯤꯡꯒꯤ ꯃꯁꯤꯡ ꯒꯦꯝ ꯌꯦꯡꯈꯤ: ꯃꯁꯤꯡ ꯑꯃꯥ ꯊꯣꯀꯄꯒꯥ ꯂꯣꯌꯅꯅ ꯃꯗꯨꯗ ꯊꯝꯕ ꯁꯦꯜ ꯌꯥꯝꯅꯥ ꯍꯟꯊꯔꯀꯈꯤ ꯑꯃꯁꯨꯡ ꯍꯟꯅꯥ ꯐꯪꯅꯕ ꯊꯥ ꯀꯌꯥ ꯆꯪꯈꯤ, ꯗ꯭ꯔꯣ ꯑꯗꯨꯒꯤ ꯅꯤꯡꯁꯤꯡꯕ ꯑꯃꯠꯇ ꯂꯩꯇꯕꯁꯨ꯫ ꯆꯦꯟ, ꯃꯣꯁ꯭ꯀꯣꯋꯤꯠꯖ ꯑꯃꯁꯨꯡ ꯁꯨ (2016) ꯅ ꯄ꯭ꯔꯣꯐꯦꯁꯅꯦꯜꯁꯤꯡꯒꯤ ꯃꯔꯛꯇꯁꯨ ꯃꯁꯤ ꯐꯪꯈꯤ꯫ ꯌꯨꯅꯥꯏꯇꯦꯗ ꯁ꯭ꯇꯦꯇꯁꯀꯤ ꯑꯦꯁꯥꯏꯂꯝ ꯖꯖꯁꯤꯡꯅ ꯃꯃꯥꯡꯒꯤ ꯀꯦꯁ ꯑꯗꯨ ꯌꯥꯔꯕꯗ ꯀꯦꯁ ꯑꯃꯥ ꯌꯥꯗꯕꯒꯤ ꯈꯨꯗꯣꯡꯆꯥꯕ ꯄꯔꯁꯦꯟꯇꯦꯖ ꯄꯣꯏꯟꯠ 3.3 ꯐꯥꯑꯣꯕ ꯍꯦꯟꯈꯤ꯫ ꯕꯦꯁꯕꯣꯜ ꯑꯝꯄꯥꯌꯔꯁꯤꯡꯅ ꯁ꯭ꯇ꯭ꯔꯥꯏꯛ ꯑꯃꯥ ꯀꯧꯔꯕꯥ ꯃꯇꯨꯡꯗ ꯑꯃꯨꯛ ꯍꯟꯅꯥ ꯀꯧꯕꯒꯤ ꯈꯨꯗꯣꯡꯆꯥꯕ ꯄꯣꯏꯟꯠ 1.5 ꯍꯟꯊꯈꯤ, ꯑꯃꯁꯨꯡ ꯈꯟꯊꯕ ꯀꯠꯊꯣꯀꯄ ꯄꯤꯆꯁꯤꯡꯗ ꯃꯗꯨꯒꯤ ꯑꯅꯤ ꯊꯥꯛꯇꯒꯤ ꯍꯦꯟꯅꯥ ꯍꯟꯊꯈꯤ꯫ ꯐ꯭ꯂꯦꯠ ꯐꯤ ꯄꯤꯕ ꯂꯣꯟ ꯑꯣꯐꯤꯁꯔꯁꯤꯡꯒꯥ ꯇꯧꯈꯤꯕ ꯐꯤꯜꯗ ꯑꯦꯛꯁꯄꯦꯔꯤꯃꯦꯟꯠ ꯑꯃꯗ ꯋꯥꯔꯦꯄꯁꯤꯡꯒꯤ 9% ꯐꯥꯑꯣꯕ ꯃꯑꯣꯡ ꯑꯁꯤꯅ ꯑꯣꯟꯊꯣꯀꯈꯤ꯫ ꯀꯦꯁꯁꯤꯡ ꯔꯦꯟꯗꯝ ꯃꯊꯪ ꯃꯊꯪꯗ ꯂꯥꯀꯈꯤ, ꯃꯔꯝ ꯑꯗꯨꯅ ꯑꯔꯣꯏꯕ ꯋꯥꯔꯦꯞ ꯑꯗꯨꯅ ꯃꯊꯪꯒꯤ ꯑꯗꯨꯒꯤ ꯃꯇꯥꯡꯗ ꯀꯔꯤꯁꯨ ꯍꯥꯌꯗꯦ, ꯑꯔꯣꯏꯕ ꯁ꯭ꯄꯤꯟ ꯑꯗꯨꯅ ꯃꯊꯪꯒꯤ ꯁ꯭ꯄꯤꯟꯒꯤ ꯃꯇꯥꯡꯗ ꯀꯔꯤꯁꯨ ꯍꯥꯌꯗꯕꯒꯨꯝꯅ꯫

ꯈꯟꯊꯕ ꯀꯠꯊꯣꯀꯄ ꯄꯤꯆꯁꯤꯡ ꯋꯥꯌꯦꯜ ꯇꯧꯔꯤꯕ ꯑꯝꯄꯥꯌꯔꯁꯤꯡꯅ ꯁ꯭ꯇ꯭ꯔꯥꯏꯛ ꯑꯃꯥ ꯀꯧꯔꯕꯥ ꯃꯇꯨꯡꯗ ꯑꯃꯨꯛ ꯍꯟꯅꯥ ꯀꯧꯕꯒꯤ ꯈꯨꯗꯣꯡꯆꯥꯕ ꯍꯟꯊꯈꯤ꯫

ꯑꯣꯟꯊꯣꯛꯂꯕ ꯖꯨꯌꯥ ꯁꯥꯟꯅꯔꯤꯕꯒꯤ ꯑꯔꯥꯟꯕ ꯋꯥꯈꯜ

ꯐꯤꯂꯣꯁꯣꯐꯔ ꯏꯌꯥꯟ ꯍꯦꯀꯤꯡ (Ian Hacking, 1987) ꯅ ꯑꯍꯨꯃꯁꯨꯕ ꯃꯈꯜ ꯑꯃꯒꯤ ꯃꯃꯤꯡ ꯊꯣꯅꯈꯤ꯫ ꯀꯅꯥꯒꯨꯝꯕ ꯑꯃꯥ ꯀꯣꯊꯥꯡ ꯑꯃꯗ ꯆꯉꯂꯛꯇꯨꯅ ꯗꯥꯏꯁ ꯑꯅꯤ ꯗꯕꯜ ꯁꯤꯛꯁ ꯊꯣꯀꯄ ꯎꯏ ꯑꯃꯁꯨꯡ ꯃꯈꯣꯌ ꯃꯃꯥꯡꯗ ꯑꯃꯨꯛ ꯀꯌꯥ ꯊꯥꯗꯣꯛꯂꯝꯂꯒꯅꯤ ꯍꯥꯌꯅ ꯋꯥꯔꯦꯞ ꯂꯧꯏ꯫ ꯊꯥꯗꯣꯀꯄ ꯈꯨꯗꯤꯡꯃꯛꯇ ꯗꯕꯜ ꯁꯤꯛꯁ ꯊꯣꯛꯄꯒꯤ ꯈꯨꯗꯣꯡꯆꯥꯕ ꯃꯥꯟꯅꯩ, ꯅꯨꯃꯤꯗꯥꯡꯒꯤ ꯑꯍꯥꯅꯕ ꯑꯣꯏꯔꯕꯁꯨ ꯂꯤꯁꯤꯡꯁꯨꯕ ꯑꯣꯏꯔꯕꯁꯨ, ꯃꯔꯝ ꯑꯗꯨꯅ ꯎꯈꯤꯕ ꯑꯗꯨꯅ ꯁꯥꯟꯅꯕ ꯑꯗꯨ ꯀꯌꯥ ꯁꯥꯡꯅ ꯆꯠꯂꯤꯕꯒꯦ ꯍꯥꯌꯕꯒꯤ ꯃꯇꯥꯡꯗ ꯀꯔꯤꯁꯨ ꯍꯥꯌꯗꯦ꯫ ꯔꯨꯂꯦꯠꯇ ꯃꯁꯤ ꯑꯉꯥꯡꯕ ꯅꯤꯄꯥꯟ ꯎꯠꯂꯤꯕ ꯕꯣꯔꯗ ꯑꯃꯗ ꯂꯥꯀꯄ ꯑꯃꯁꯨꯡ ꯃꯈꯣꯌ ꯊꯣꯛꯅꯕ ꯇꯦꯕꯜ ꯑꯗꯨ ꯄꯨꯡ ꯀꯌꯥ ꯀꯣꯏꯔꯝꯂꯒꯅꯤ ꯍꯥꯌꯅ ꯋꯥꯔꯦꯞ ꯂꯧꯕ ꯁꯥꯟꯅꯔꯤꯕ ꯑꯗꯨꯅꯤ꯫ ꯃꯍꯧꯁꯥꯒꯤ ꯑꯔꯥꯟꯕ ꯋꯥꯈꯂꯅ ꯍꯥꯟꯅꯒꯤ ꯑꯗꯨ ꯃꯊꯪꯒꯤ ꯁ꯭ꯄꯤꯟꯗ ꯄꯥꯔꯤ; ꯃꯁꯤꯅꯗꯤ ꯈꯔꯥ ꯈꯛꯇꯗ ꯎꯕ ꯐꯪꯕ ꯃꯤꯠꯌꯦꯡ ꯑꯃꯥ ꯀꯅꯥꯒꯨꯝꯕ ꯑꯃꯠꯇꯅ ꯎꯈꯤꯗꯕ ꯍꯥꯟꯅꯒꯤ ꯊꯧꯗꯣꯛ ꯑꯃꯗ ꯄꯥꯔꯤ꯫

ꯃꯁꯤ ꯊꯥꯖꯈꯤꯕ ꯁꯥꯏꯀꯣꯂꯣꯖꯤꯁ꯭ꯠ ꯑꯃꯥ

ꯑꯔꯥꯟꯕ ꯋꯥꯈꯜ ꯑꯁꯤꯒꯤ ꯃꯍꯩ ꯇꯃꯈꯤꯕ ꯉꯥꯛꯁꯦꯜꯂꯤꯕꯁꯤꯡ ꯂꯩꯈꯤ꯫ ꯖꯔꯃꯟ ꯁꯥꯏꯀꯣꯂꯣꯖꯤꯁ꯭ꯠ ꯀꯥꯔꯜ ꯃꯥꯔꯕꯦꯅ ꯑꯃꯃꯃꯗ ꯄꯣꯛꯄ 49,152 ꯂꯩꯕ ꯔꯦꯖꯤꯁ꯭ꯇꯔ ꯃꯔꯤ ꯌꯦꯡꯈꯤ, ꯃꯈꯥ ꯆꯠꯅꯅ ꯅꯨꯄꯥꯃꯆꯥ ꯅꯠꯔꯒ ꯅꯨꯄꯤꯃꯆꯥꯒꯤ ꯈ꯭ꯕꯥꯏꯗꯒꯤ ꯁꯥꯡꯕ ꯁ꯭ꯇ꯭ꯔꯤꯛ 17 ꯅꯤ ꯍꯥꯌꯅ ꯐꯪꯈꯤ, ꯑꯃꯁꯨꯡ ꯁꯥꯡꯕ ꯁ꯭ꯇ꯭ꯔꯤꯛꯁꯤꯡ ꯂꯥꯛꯅ ꯌꯥꯍꯜꯂꯤꯕꯗꯒꯤ ꯍꯦꯟꯅꯥ ꯈꯔꯥ ꯈꯛꯇꯗ ꯊꯣꯀꯏ, ꯃꯔꯝ ꯑꯗꯨꯅ ꯁ꯭ꯇ꯭ꯔꯤꯛ ꯑꯃꯅ ꯑꯇꯣꯞꯄ ꯃꯍꯩ ꯑꯗꯨ ꯍꯦꯟꯅꯥ ꯊꯣꯛꯄ ꯌꯥꯍꯜꯂꯤ ꯍꯥꯌꯅ ꯋꯥꯔꯦꯞ ꯂꯧꯈꯤ꯫ ꯂꯥꯛꯈꯛꯇꯅ ꯑꯇꯣꯞꯄ ꯍꯥꯌꯔꯤ: ꯄꯣꯛꯄ 196,608 ꯗ 17 ꯅꯠꯔꯒ ꯍꯦꯟꯕꯒꯤ ꯁ꯭ꯇ꯭ꯔꯤꯛ ꯑꯃꯥ ꯃꯇꯝ ꯃꯉꯥꯗꯒꯤ ꯃꯔꯤ ꯃꯔꯛꯇ ꯊꯣꯀꯏ꯫ ꯃꯥꯔꯕꯦꯅ ꯐꯪꯈꯤꯕ ꯑꯗꯨ ꯔꯦꯟꯗꯝ ꯃꯊꯪ ꯃꯊꯪ ꯑꯃꯒꯤ ꯃꯑꯣꯡ ꯑꯗꯨꯃꯛꯇꯅꯤ꯫ ꯑꯦꯞꯁ꯭ꯇꯥꯏꯟ (2013) ꯅ ꯋꯥꯐꯝ ꯑꯁꯤ ꯑꯃꯨꯛ ꯍꯟꯅꯥ ꯍꯥꯌꯔꯤ; “ꯔꯨꯂꯦꯠꯇ ꯁ꯭ꯇ꯭ꯔꯤꯛ ꯊꯣꯛꯄꯒꯤ ꯈꯨꯗꯣꯡꯆꯥꯕ” ꯂꯃꯥꯏꯅ ꯔꯨꯂꯦꯠꯀꯤ ꯃꯈꯜ ꯄꯤꯔꯤ꯫

ꯀꯥꯔꯜ ꯃꯥꯔꯕꯦꯅ ꯅꯨꯄꯥꯃꯆꯥ ꯅꯠꯔꯒ ꯅꯨꯄꯤꯃꯆꯥꯒꯤ ꯁꯥꯡꯕ ꯁ꯭ꯇ꯭ꯔꯤꯛ ꯊꯤꯅꯕ ꯄꯣꯛꯄꯒꯤ ꯔꯦꯖꯤꯁ꯭ꯇꯔꯁꯤꯡ ꯌꯦꯡꯁꯤꯜꯂꯤ꯫

ꯑꯔꯥꯟꯕ ꯋꯥꯈꯜ ꯑꯁꯤ ꯆꯠꯂꯣꯏꯗꯕ ꯃꯐꯝ

ꯆꯛꯔ ꯑꯗꯨ ꯁꯛꯇꯝ ꯑꯣꯏꯅ ꯕꯥꯏꯌꯥꯁ ꯂꯩꯔꯕꯗꯤ ꯍꯥꯟꯅꯒꯤ ꯁ꯭ꯄꯤꯟꯁꯤꯡꯅ ꯈꯉꯍꯟꯕ ꯄꯤꯒꯅꯤ, ꯃꯔꯃꯗꯤ ꯃꯈꯣꯌꯅ ꯂꯥꯛꯀꯤ ꯃꯇꯥꯡꯗ ꯅꯠꯇꯅ ꯄꯣꯀꯦꯠꯁꯤꯡꯒꯤ ꯃꯇꯥꯡꯗ ꯁꯥꯛꯁꯤ ꯄꯤꯒꯅꯤ꯫ ꯃꯁꯤ ꯂꯦꯕꯀꯤ ꯍꯤꯔꯝꯅꯤ, ꯑꯃꯁꯨꯡ ꯀꯔꯤꯒꯨꯝꯕ ꯑꯃꯥ ꯍꯥꯌꯅꯕ ꯈꯉꯖꯤꯜꯂꯕ ꯆꯛꯔ ꯑꯃꯗꯒꯤ ꯁ꯭ꯄꯤꯟ ꯂꯤꯁꯤꯡ ꯀꯌꯥ ꯃꯊꯧ ꯇꯥꯏ꯫ ꯈꯉꯗꯕ ꯆꯛꯔ ꯑꯃꯗ ꯑꯉꯥꯡꯕ ꯇꯔꯥꯒꯤ ꯁ꯭ꯇ꯭ꯔꯤꯛ ꯑꯃꯒꯤꯗꯃꯛ ꯕꯥꯏꯌꯥꯁꯀꯤ ꯃꯔꯝ ꯑꯁꯤ ꯂꯥꯛꯀꯤ ꯃꯔꯃꯗꯒꯤ ꯌꯥꯝꯅꯥ ꯍꯦꯟꯅꯥ ꯊꯣꯛꯄ ꯌꯥꯗꯦ꯫

ꯁꯦꯝꯄꯜ ꯁꯥꯏꯖ

ꯋꯥꯍꯪꯁꯤꯡ

ꯑꯔꯥꯟꯕ ꯋꯥꯈꯜ ꯑꯁꯤ ꯔꯨꯂꯦꯠꯀꯤ ꯃꯇꯥꯡꯗꯈꯛꯇꯔꯥ?

ꯅꯠꯇꯦ꯫ ꯃꯁꯤ ꯃꯔꯤ ꯂꯩꯅꯗꯅ ꯍꯟꯖꯤꯟ ꯍꯟꯖꯤꯟ ꯊꯣꯀꯄ ꯊꯧꯗꯣꯛ ꯈꯨꯗꯤꯡꯃꯛꯇ ꯆꯠꯂꯤ: ꯗꯥꯏꯁ, ꯀꯣꯏꯟ, ꯂꯣꯇꯔꯤꯒꯤ ꯃꯁꯤꯡꯁꯤꯡ꯫

ꯑꯩꯅ ꯁ꯭ꯄꯤꯟ 1,000 ꯒꯤ ꯑꯃꯨꯕꯗ ꯕꯦꯠ ꯊꯝꯂꯕꯗ ꯑꯉꯥꯡꯕ ꯑꯃꯁꯨꯡ ꯑꯃꯨꯕ ꯆꯞ ꯃꯥꯟꯅꯔꯛꯂꯣꯏꯗ꯭ꯔꯥ?

ꯆꯥꯡꯁꯤꯡ ꯑꯗꯨ ꯅꯛꯂꯛꯀꯅꯤ꯫ ꯅꯍꯥꯛꯀꯤ ꯃꯍꯩ ꯑꯗꯨ ꯍꯧꯖꯤꯀꯁꯨ ꯅꯍꯥꯛꯅ ꯊꯝꯂꯤꯕ ꯁꯦꯜꯒꯤ −2.70% ꯃꯔꯛꯇꯅꯤ꯫

ꯑꯦꯚꯔꯦꯖꯀꯤ ꯅꯤꯌꯝꯗꯤ ꯀꯔꯝꯅꯣ?

ꯑꯦꯚꯔꯦꯖꯀꯤ ꯅꯤꯌꯝ ꯂꯩꯇꯦ꯫ ꯑꯆꯧꯕ ꯃꯁꯤꯡꯒꯤ ꯅꯤꯌꯝ ꯂꯩ, ꯑꯃꯁꯨꯡ ꯃꯁꯤ ꯌꯥꯎꯊꯣꯀꯄꯅ ꯊꯕꯛ ꯇꯧꯏ꯫

ꯃꯦꯊꯃꯦꯇꯤꯛꯁꯀꯥ ꯁꯥꯟꯅꯕ

ꯃꯁꯤꯁꯤꯡ ꯑꯍꯥꯅꯕꯗ ꯅꯍꯥꯛ ꯃꯁꯥꯃꯛꯅ ꯍꯣꯠꯅꯕꯤꯌꯨ꯫ ꯄꯥꯎꯈꯨꯝ ꯈꯨꯗꯤꯡꯃꯛ ꯊꯨꯡꯗꯨꯅ ꯊꯝꯂꯤ; ꯁꯦꯝ ꯁꯥꯔꯕ ꯃꯇꯃꯗ ꯍꯥꯡꯗꯣꯛꯄꯤꯌꯨ꯫

ꯀꯣꯏꯟ ꯑꯃꯥ ꯑꯃꯨꯛ 10 ꯆꯥꯟꯊꯔꯕꯗ ꯍꯦꯗ 7 ꯑꯃꯁꯨꯡ ꯇꯦꯜ 3 ꯎꯠꯂꯤ꯫ ꯑꯃꯨꯛ 1,000 ꯆꯥꯟꯊꯔꯕꯗ ꯍꯦꯗ 517 ꯑꯃꯁꯨꯡ ꯇꯦꯜ 483 ꯎꯠꯂꯤ꯫ ꯇꯦꯂꯁꯤꯡꯅ ꯃꯇꯨꯡ ꯏꯟꯅ ꯌꯧꯔꯛꯂꯕꯔꯥ?
ꯄꯥꯎꯈꯨꯝ ꯎꯠꯄ
ꯄꯥꯎꯈꯨꯝ ꯅꯠꯇꯦ꯫ ꯈꯦꯠꯅꯕ ꯑꯗꯨ 4 ꯗꯒꯤ 34 ꯐꯥꯑꯣꯕ ꯍꯦꯅꯒꯠꯂꯛꯂꯦ꯫ ꯔꯦꯁꯤꯑꯣ ꯑꯗꯨ ꯈꯛꯇꯅ ꯆꯞ ꯃꯥꯟꯅꯕꯒꯤ ꯃꯅꯥꯛꯇ ꯂꯥꯀꯈꯤ꯫
ꯍꯦꯗ ꯑꯃꯁꯨꯡ ꯇꯦꯂꯒꯤ ꯔꯦꯁꯤꯑꯣ ꯑꯗꯨ 7/3, ꯈꯟꯊꯕꯗ 2.33 ꯗꯒꯤ 517/483, ꯈꯟꯊꯕꯗ 1.07 ꯐꯥꯑꯣꯕ ꯍꯟꯊꯔꯛꯂꯦ꯫ ꯃꯗꯨ ꯑꯆꯧꯕ ꯃꯁꯤꯡꯒꯤ ꯅꯤꯌꯝꯃꯦꯊꯃꯦꯇꯤꯛꯁꯑꯆꯧꯕ ꯃꯁꯤꯡꯒꯤ ꯅꯤꯌꯝꯍꯣꯠꯅꯕꯒꯤ ꯃꯁꯤꯡ ꯍꯦꯅꯒꯠꯂꯀꯄꯒ ꯂꯣꯌꯅꯅ ꯃꯔꯤ ꯂꯩꯅꯗꯕ ꯃꯍꯩꯁꯤꯡꯒꯤ ꯑꯦꯚꯔꯦꯖ ꯑꯗꯨ ꯐꯪꯒꯗꯕ ꯃꯃꯂꯗ ꯅꯛꯂꯛꯏ꯫ꯃꯄꯨꯡ ꯄꯥꯕꯤꯌꯨ → ꯊꯕꯛ ꯇꯧꯔꯤꯕꯅꯤ꯫
ꯃꯈꯣꯌꯒꯤ ꯃꯔꯛꯇ ꯂꯩꯕ ꯈꯦꯠꯅꯕ ꯑꯗꯨ ꯍꯦꯅꯒꯠꯂꯛꯂꯦ, 4 ꯗꯒꯤ 34 ꯐꯥꯑꯣꯕ꯫ ꯆꯨꯝꯃꯤꯟꯅꯕ ꯀꯣꯏꯟ ꯑꯃꯗ ꯑꯃꯨꯛ 1,000 ꯒꯤ ꯃꯇꯨꯡꯗ ꯈꯟꯊꯕꯗ 30 ꯒꯤ ꯈꯦꯠꯅꯕ ꯑꯁꯤ ꯃꯍꯧꯁꯥꯒꯤꯅꯤ: ꯃꯍꯧꯁꯥꯒꯤ ꯈꯦꯠꯅꯕ ꯑꯁꯤ ꯆꯥꯟꯊꯕꯒꯤ ꯃꯁꯤꯡꯒꯤ ꯁ꯭ꯀ꯭ꯋꯦꯌꯔ ꯔꯨꯠꯀꯥ ꯈꯟꯊꯕꯗ ꯆꯥꯟꯅꯅ ꯍꯦꯅꯒꯠꯂꯛꯀꯅꯤ, ꯑꯗꯨꯒꯥ ꯔꯦꯁꯤꯑꯣ ꯑꯗꯨ 1 ꯒꯤ ꯃꯅꯥꯛꯇ ꯂꯦꯞꯂꯛꯀꯅꯤ꯫
ꯀꯔꯤꯒꯨꯝꯕ ꯑꯃꯠꯇꯅ ꯇꯦꯂꯁꯤꯡ ꯍꯜꯂꯛꯍꯟꯈꯤꯗꯦ꯫ ꯑꯍꯥꯅꯕꯗ ꯍꯦꯟꯅꯥ ꯂꯩꯔꯝꯕ ꯍꯦꯗꯁꯤꯡ ꯑꯗꯨ ꯃꯊꯪꯒꯤ ꯆꯥꯟꯊꯕ 990 ꯅ ꯁꯦꯝꯖꯤꯟꯈꯤꯕꯅꯤ, ꯁꯦꯃꯗꯣꯛꯈꯤꯕ ꯅꯠꯇꯦ꯫
ꯀꯣꯏꯟ ꯑꯃꯥ ꯑꯃꯨꯛ ꯃꯔꯤ ꯆꯥꯟꯊꯕꯤꯌꯨ ꯑꯃꯁꯨꯡ ꯍꯦꯗ ꯑꯃꯒꯤ ꯃꯇꯨꯡꯗ ꯊꯨꯅ ꯂꯥꯀꯄ ꯆꯥꯟꯊꯕꯁꯤꯡ ꯈꯛꯇ ꯌꯦꯡꯕꯤꯌꯨ꯫ ꯃꯈꯣꯌꯒꯤ ꯁꯔꯨꯛ ꯀꯌꯥ ꯍꯦꯗꯅꯣ? ꯐꯪꯕ ꯌꯥꯕ ꯁꯤꯛꯋꯦꯟꯁ 16 ꯒꯤ ꯈꯨꯗꯤꯡꯃꯛꯀꯤꯗꯃꯛ ꯍꯤꯁꯥꯕ ꯇꯧꯕꯤꯌꯨ ꯑꯃꯁꯨꯡ ꯁꯔꯨꯛꯁꯤꯡꯒꯤ ꯑꯦꯚꯔꯦꯖ ꯂꯧꯕꯤꯌꯨ꯫ ꯃꯗꯨ 50% ꯔꯥ?
ꯄꯥꯎꯈꯨꯝ ꯎꯠꯄ
ꯄꯥꯎꯈꯨꯝ ꯅꯠꯇꯦ꯫ ꯃꯗꯨ 17/42, ꯈꯟꯊꯕꯗ 40.5% ꯅꯤ꯫ ꯃꯑꯣꯡ ꯑꯁꯤꯗ ꯌꯦꯡꯂꯕꯗ, ꯆꯨꯝꯃꯤꯟꯅꯕ ꯀꯣꯏꯟ ꯑꯃꯅ ꯍꯦꯗ ꯑꯃꯒꯤ ꯃꯇꯨꯡꯗ ꯏꯪꯂꯛꯂꯤꯕꯒꯨꯝ ꯎꯏ꯫
ꯁꯤꯛꯋꯦꯟꯁ 16 ꯂꯤꯁ꯭ꯠ ꯇꯧꯕꯤꯌꯨ꯫ ꯃꯈꯣꯌꯒꯤ ꯑꯅꯤ, TTTT ꯑꯃꯁꯨꯡ TTTH, ꯗ ꯑꯍꯥꯅꯕ ꯆꯥꯟꯊꯕ ꯑꯍꯨꯃꯒꯤ ꯃꯅꯨꯡꯗ ꯍꯦꯗ ꯑꯃꯠꯇꯥ ꯂꯩꯇꯦ, ꯃꯔꯝ ꯑꯗꯨꯅ ꯍꯦꯗ ꯑꯃꯒꯤ ꯃꯇꯨꯡꯗ ꯀꯔꯤꯁꯨ ꯂꯥꯀꯄ ꯂꯩꯇꯦ; 14 ꯊꯃꯏ꯫
ꯈꯨꯗꯤꯡꯃꯛꯇ, ꯍꯦꯗ ꯑꯃꯒꯤ ꯃꯇꯨꯡꯗ ꯂꯥꯀꯄ ꯆꯥꯟꯊꯕꯁꯤꯡ ꯂꯧꯕꯤꯌꯨ ꯑꯃꯁꯨꯡ ꯃꯈꯣꯌꯒꯤ ꯁꯔꯨꯛ ꯀꯌꯥ ꯍꯦꯗꯅꯣ ꯊꯤꯕꯤꯌꯨ꯫ HHHH ꯅ 3 ꯒꯤ ꯃꯅꯨꯡꯗꯒꯤ 3 ꯄꯤ꯫ HHHT ꯅ 3 ꯒꯤ ꯃꯅꯨꯡꯗꯒꯤ 2 ꯄꯤ꯫ HTHT ꯅ 2 ꯒꯤ ꯃꯅꯨꯡꯗꯒꯤ 0 ꯄꯤ꯫ 14 ꯄꯨꯝꯅꯃꯛ ꯌꯦꯡꯂꯕꯗ: ꯁꯤꯛꯋꯦꯟꯁ ꯇꯔꯨꯛꯅ 0 ꯄꯤ, ꯃꯔꯤꯅ 1/2 ꯄꯤ, ꯑꯃꯅ 2/3 ꯄꯤ ꯑꯃꯁꯨꯡ ꯑꯍꯨꯃꯅ 1 ꯄꯤ (HHHH, THHH ꯑꯃꯁꯨꯡ TTHH)꯫
ꯁꯔꯨꯛꯁꯤꯡ ꯄꯨꯟꯁꯤꯟꯕꯤꯌꯨ: 4 × 1/2 + 2/3 + 3 = 17/3꯫ 14 ꯅ ꯌꯦꯟꯕꯤꯌꯨ: 17/42 ≈ 40.5%꯫
ꯆꯥꯟꯊꯕ ꯑꯃꯠꯇꯅ ꯇꯦꯜ ꯃꯥꯌꯀꯩ ꯂꯧꯗꯦ; ꯈꯨꯗꯤꯡꯃꯛ 50–50 ꯅꯤ꯫ ꯇꯦꯟꯊꯕ ꯑꯁꯤ ꯁꯤꯛꯋꯦꯟꯁ ꯑꯃꯃꯃꯒꯤ ꯑꯦꯚꯔꯦꯖ ꯂꯧꯕꯗꯒꯤ ꯂꯥꯀꯏ: ꯍꯦꯗꯅ ꯊꯜꯂꯕ ꯁꯤꯛꯋꯦꯟꯁ ꯑꯃꯗ ꯌꯦꯡꯒꯗꯕ ꯆꯥꯟꯊꯕ ꯀꯌꯥ ꯂꯩ ꯑꯗꯨꯕꯨ ꯑꯃꯨꯛ ꯈꯛ ꯊꯤ, ꯍꯦꯗ ꯑꯃꯈꯛ ꯂꯩꯕ ꯁꯤꯛꯋꯦꯟꯁ ꯑꯃꯒꯨꯝꯅ꯫ ꯃꯤꯂꯔ ꯑꯃꯁꯨꯡ ꯁꯥꯟꯖꯨꯔꯖꯣ (2018) ꯅ 1985 ꯒꯤ ꯍꯣꯠ ꯍꯦꯟꯗ ꯊꯤꯖꯤꯟꯕ ꯑꯗꯨꯅ ꯃꯁꯤꯒꯤ ꯕꯥꯁ꯭ꯀꯦꯠꯕꯣꯜ ꯁꯥꯟꯅꯔꯤꯕꯁꯤꯡ ꯃꯑꯣꯡ ꯑꯁꯤꯗ ꯌꯦꯡꯈꯤ ꯍꯥꯌꯅ ꯎꯠꯈꯤ, ꯃꯔꯝ ꯑꯗꯨꯅ ꯈꯨꯗꯣꯡꯆꯥꯕꯗꯒꯤ ꯍꯦꯟꯅꯥ ꯁ꯭ꯇ꯭ꯔꯤꯛ ꯂꯩꯗꯕꯒꯨꯝ ꯎꯔꯝꯕ ꯁꯥꯟꯅꯔꯤꯕꯁꯤꯡ ꯑꯁꯦꯡꯕꯗ ꯈꯔꯥ ꯍꯦꯟꯅꯥ ꯁ꯭ꯇ꯭ꯔꯤꯛ ꯂꯩꯔꯝꯃꯤ꯫

ꯅꯣꯛꯅꯕꯒꯤ ꯀꯃꯤꯛ

$ꯌꯥꯎꯊꯣꯀꯄꯅꯤ, ꯆꯨꯃꯊꯣꯀꯄ ꯅꯠꯇꯦ꯫ ꯆꯛꯔꯅ ꯀꯅꯥꯒꯨꯝꯕ ꯑꯃꯒꯤꯁꯨ ꯁꯦꯜ ꯄꯤꯒꯗꯕ ꯂꯩꯇꯦ꯫$

ꯌꯥꯎꯊꯣꯀꯄꯅꯤ, ꯆꯨꯃꯊꯣꯀꯄ ꯅꯠꯇꯦ꯫ ꯆꯛꯔꯅ ꯀꯅꯥꯒꯨꯝꯕ ꯑꯃꯒꯤꯁꯨ ꯁꯦꯜ ꯄꯤꯒꯗꯕ ꯂꯩꯇꯦ꯫

ꯍꯧꯔꯛꯐꯃꯁꯤꯡ

Feller, W. An Introduction to Probability Theory and Its Applications, Vol. 1. Wiley, 3 ꯁꯨꯕ ꯑꯦꯗꯤꯁꯟ, 1968꯫ ꯖꯨꯌꯥ ꯁꯥꯟꯅꯔꯤꯕꯒꯤ ꯃꯥꯡꯍꯟ ꯇꯥꯀꯍꯟꯕ (gambler’s ruin), ꯆꯦꯞꯇꯔ XIV꯫
Schwartz, D. G. Roll the Bones: The History of Gambling. Gotham, 2006꯫
Ethier, S. N. The Doctrine of Chances: Probabilistic Aspects of Gambling. Springer, 2010꯫ ꯆꯦꯞꯇꯔ 13, ꯔꯨꯂꯦꯠ꯫
Epstein, R. A. The Theory of Gambling and Statistical Logic, 2nd ed. Academic Press, 2013꯫
Croson, R. & Sundali, J. “The gambler’s fallacy and the hot hand: empirical data from casinos.” Journal of Risk and Uncertainty 30(3), 2005꯫
Chen, D. L., Moskowitz, T. J. & Shue, K. “Decision making under the gambler’s fallacy: evidence from asylum judges, loan officers, and baseball umpires.” Quarterly Journal of Economics 131(3), 2016; ꯃꯁꯤꯡꯁꯤꯡ NBER Working Paper 22026 ꯗꯒꯤ꯫
Clotfelter, C. T. & Cook, P. J. “The ‘gambler’s fallacy’ in lottery play.” Management Science 39(12), 1993꯫
Gilovich, T., Vallone, R. & Tversky, A. “The hot hand in basketball: on the misperception of random sequences.” Cognitive Psychology 17(3), 1985꯫
Miller, J. B. & Sanjurjo, A. “Surprised by the hot hand fallacy? A truth in the law of small numbers.” Econometrica 86(6), 2018꯫
Hacking, I. “The inverse gambler’s fallacy: the argument from design. The anthropic principle applied to Wheeler universes.” Mind 96(383), 1987꯫

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