In the article "Foods, Fortificants, and Supplements: Where Do Americans Get Their Nutrients?" researchers analyze the nutrient

Answer:

0.035 < 0.05

Thus,

the p-value is less than the significance level

Consequently, we reject the null hypothesis and accept the alternative hypothesis, concluding that there is a notable difference in the proportion of U.S. women and men consuming the recommended calcium levels.

Step-by-step explanation:

When testing a hypothesis, the first task is to establish the null and alternative hypotheses.

The null hypothesis represents a stance of no significant difference between two proportions being analyzed.

On the other hand, the alternative hypothesis argues that there is, in fact, a significant difference between those two proportions.

In this scenario, we are examining the proportion of women and men in the U.S. who meet the recommended calcium intake.

Our goal is to determine if a significant difference exists between the proportions of U.S. women and men who consume the recommended calcium levels.

If we denote the proportion of U.S. women who meet the calcium recommendations as p₁

And

the proportion of U.S. men as p₂

The difference can be represented as

μ₀ = p₁ - p₂

The null and alternative hypotheses can be mathematically stated as

Null hypothesis: no significant difference between women and men regarding recommended calcium intake levels

H₀: μ₀ = 0

or

H₀: p₁ = p₂

Hₐ: μ₀ ≠ 0

or

Hₐ: p₁ ≠ p₂

Now examining the p-value,

It calculates to 0.035 while the significance threshold is 5%. What does this p-value signify?

When the (p-value > significance level), we cannot reject the null hypothesis and when the (p-value < significance level), we reject the null hypothesis in favor of the alternative hypothesis.

For this question, the significance level is set at 5% or 0.05

p-value = 0.035

0.035 < 0.05

Thus,

the p-value is below the significance threshold

I hope this is helpful!!!