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Explanation: The Central Limit Theorem (CLT) states that, regardless of the shape of the population distribution , the distribution of sample means will tend to be normal (bell-shaped) if the sample size is sufficiently large (typically n ≥ 30 ). Here, despite the right-skewed nature of the claim amounts , the repeated sampling process ensures that the sample means approximate a normal distribution , allowing for reliable statistical inferences.
I. p2 – 15p + 56 = 0
II. q2 + 2q – 63 = 0
I. 27x² + 120x + 77 = 0
II. 56y² + 117y + 36 = 0
I. 6y2 – 23y + 20 = 0
II. 4x2 – 24 x + 35 = 0
I. y/16 = 4/y
II. x3= (2 ÷ 50) × (2500 ÷ 50) × 42× (192 ÷ 12)
Solve the given two equations and answer the two questions that follow as per the instructions given below.
I. (1/4) + 7.5p(-2) = 3.62...
I. 6x2- 47x + 77 =0
II. 6y2- 35y + 49 = 0
I. 15y2+ 26y + 8 = 0
II. 20x2+ 7x – 6 = 0
I. 6x² + 77x + 121 = 0
II. y² + 9y - 22 = 0
I. 6p2 – 7p = 5p – 7p2 + 25
II. 11q2 – 63q + 90 = 0
I. 3y2+ 16y + 16 = 0
II. 2x2+ 19x + 45 = 0