HI I need help on what is the right answer for this 2 activities. No need for explanation. Other concerns will be in the comment section. I hope the you can help me

(Week 7) Note: Study pages 235-249 of your self-learning module to be able to answer the activity. You may use other reference materials, physical or online, if you deem the module insufficient. Part I. Choose from the pool of words/mathematical formulas inside the box to complete the following paragraph on the important properties of the Sampling Distribution of the Sample Mean. Then write the corresponding words below each term to complete the sentence. (3 points each) If all possible sample size n are drawn from a population of size N with mean / and (1) then the sampling distribution of the sample mean has the following properties: First, the (2) of the sampling distribution of the (3) is (4) to the (5) H. That is, Hx = |1. Second, the variance of the sampling distribution of the sample mean Ov is given by: ox = ON-n The (8) n - for (6) and ON = = n N-1 for (7) of the sampling distribution of the sample mean is given by Ox = m N- for N - 1 finite population (sampling without replacement) where -is the finite population correction factor and (9) for infinite population (sampling with replacement). Mean Infinite Population Population Mean YOU SUGAR LITTLE Equal Standard Deviation Variance A YOUR WOULD Sample Mean Finite Population LIKE IN Vn COFFEE? What is the constructed sentence? (3 points) Part II. Complete the following statements. (2 points each) The Central Limit Theorem implies the important ideas in statistics: 1. When the sample size tends to infinity (a very large sample) the distribution of the sample mean X will be distributed. 2. If the sample size tends to infinity, the sample mean Hx the population mean /. 3. When the original variable is normally distributed, the distribution of the sample means will be distributed, for any sample size n. 4. When the distribution of the original variable might not be normal, a sample size of or more is needed to use a normal distribution to approximate the distribution of the sample means. The larger the sample, the better the approximation will be