F, N, K = map(int, input().split())

expectation = 0.0

for v in range(1, F + 1):
    p = (F - v + 1) / F  # Probability of getting >=v in one roll
    dp = [0.0] * (N + 1)
    dp[0] = 1.0  # Starting with 0 trials, 0 successes
    
    for i in range(1, N + 1):
        next_dp = [0.0] * (N + 1)
        for j in range(0, i + 1):
            if j > 0:
                next_dp[j] += dp[j - 1] * p
            if j <= i - 1:
                next_dp[j] += dp[j] * (1 - p)
        dp = next_dp
    
    # Sum probabilities where at least K successes
    prob = sum(dp[K:])
    expectation += prob

# Output with sufficient precision
print("{0:.15f}".format(expectation))