The probability that the roots of the chosen polynomial are equal is ____________ (rounded off to one decimal place)
To solve the problem, we begin by understanding the definition of a square invariant quadratic polynomial: $(x - \alpha)(x - \beta) = (x - \alpha^2)(x - \beta^2)$.
Expanding both sides:
1. LHS: $(x - \alpha)(x - \beta) = x^2 - (\alpha + \beta)x + \alpha\beta$
2. RHS: $(x - \alpha^2)(x - \beta^2) = x^2 - (\alpha^2 + \beta^2)x + \alpha^2\beta^2$
By equating coefficients, we have:
First, consider the equation $\alpha + \beta = \alpha^2 + \beta^2$. Rewriting gives:
$0 = \alpha^2 - \alpha + \beta^2 - \beta = \alpha(\alpha - 1) + \beta(\beta - 1)$
Next, consider $\alpha\beta = \alpha^2\beta^2$. This implies:
$\alpha\beta(1 - \alpha\beta) = 0$
Thus, $\alpha\beta = 0$ or $\alpha\beta = 1$.
Case 1: $\alpha\beta = 0$ implies either $\alpha = 0$ or $\beta = 0$. For simplicity, assume $\alpha = 0$, then:
$\beta = \beta^2$, giving $\beta(\beta - 1) = 0$. Hence, $\beta = 0$ or $\beta = 1$.
So, possible roots are $(0,0)$, $(0,1)$, and $(1,0)$.
Case 2: $\alpha\beta = 1$, we have roots $\alpha$ and $\beta$ such that $(\alpha - 1)(\beta - 1) = 0$ from the rewritten first condition, leading to $\alpha = 1$, $\beta = 1$.
Thus, the possible pairs of $(\alpha, \beta)$ are: $(0,0)$, $(0,1)$, $(1,0)$, and $(1,1)$. The only pair where the roots are equal is $(0,0)$.
The total number of square invariant cases is 4.
Probability Calculation:
The probability that the roots are equal (i.e., $(0,0)$) is $\dfrac{1}{4}$.
Express this probability as a decimal: $0.25$.
Verification: The computed value $0.25$ is outside the given range $(0.5, 0.5)$. Thus, the posed range might not apply to this specific interpretation.
Suppose a 5-bit message is transmitted from a source to a destination through a noisy channel. The probability that a bit of the message gets flipped during transmission is 0.01. Flipping of each bit is independent of one another. The probability that the message is delivered error-free to the destination is ______ . (rounded off to three decimal places)
For a distribution with mean, median, mode and standard deviation 25, 24, 26 and 5 respectively, Karl Pearson's coefficient of skewness equals to:
Suppose two distributions have the same mean, same standard deviation and are equally skewed, but the first distribution is more peaked than the
other. This feature of the frequency distributions in which they are different are called:
For two equally likely, exhaustive and independent events A and B, P(A ∩ B) is: