I believe the answer is D.
The equation Y - (-8) = -6 (x-2) is accurate, but the rest are not.
This simplifies to y + 8 = -6x + 12.
Then, applying the subtraction of 8 yields y = -6x + 4, which is the correct slope-intercept form.
Hi! The goal of the Chi-Square Goodness of Fit test is to determine if observed frequencies of a categorical variable align with the expected historical or theoretical values in the population. Having the sales proportions of the top-five compact cars, we compare them against 400 compact car sales data from Chicago to see if there are discrepancies. Specifically, we have:
- Chevy Cruze 24% ⟹ P(CC) = 0.24
- Ford Focus 21% ⟹ P(FF) = 0.21
- Hyundai Elantra 20% ⟹ P(HE) = 0.20
- Honda Civic 18% ⟹ P(HC) = 0.18
- Toyota Corolla 17% ⟹ P(TC) = 0.17
The hypotheses established are:
H₀: P(CC) = 0.24; P(FF) = 0.21; P(HE) = 0.20; P(HC) = 0.18; P(TC) = 0.17
H₁: There is a discrepancy between expected and observed outcomes.
With α set at 0.05, the statistic calculated is based on Oi (observed frequency) and Ei (expected frequency). The initial step involves calculating expected frequencies using: Ei = n * Pi, where Pi is the theoretical proportion for each category stated in the null hypothesis. The test conducted is right-tailed, and so is the p-value, calculated as: P(X²₄ ≥ 11.23) = 1 - P(X²₄ < 11.23) = 1 - 0.98 = 0.02. Since the p-value is lower than α, we reject the null hypothesis, indicating that Chicago's market shares for the five compact cars differ from those reported by Motor Trend.
Answer:
Triangles would be congruent through ASA if Angle A is equal to Angle T.
Triangles would be congruent via AAS if Angle B matches Angle P.
Step-by-step explanation:
It is established that sides AC and TQ are congruent, along with angles BCA and PQT. If angles A and T are equal, we apply the ASA theorem. Similarly, if angle B equals angle P, we reference the AAS theorem.
Since only two options need to be selected, you can conclude your options there.
If you are referring to (r+5)/mn, then:
