Let's decribe each sample:
"\\overline{X}" - sample mean
A:
"\\mu_{\\overline{X}_A}" = 1800
"\\sigma_{\\overline{X}_A}" = "\\sigma\/\\sqrt{n}" = "240\/\\sqrt{250}=15.1789"
B:
"\\mu_{\\overline{X}_B}" = 1450
"\\sigma_{\\overline{X}_B}" = "\\sigma\/\\sqrt{n}" = "150\/\\sqrt{250}=9.48683"
Let's decribe the difference between two means:
"\\mu_{{\\overline{X}_A}-{\\overline{X}_B}} = 1800-1450=350"
"\\sigma_{{\\overline{X}_A}-{\\overline{X}_B}}=17.8997,\\sqrt{\\sigma_{\\overline{X}_A}^2+\\sigma_{\\overline{X}_B}^2}=\\sqrt{15.1789^2+9.48683^2}=17.8997"
Finally, we can compute z-score:
z="\\frac{400-\\mu_{({\\overline{X}_A}-{\\overline{X}_B})}}{\\sigma_{({\\overline{X}_A}-{\\overline{X}_B})}}=\\frac{400-350}{17.8997}=2.79334"
P(x>z) = 0.0026083
Answer: 0.0026083
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