Question Solved1 Answer K-means clustering and normalization kmtest.csv: 2.000000 4.000000 3.000000 3.000000 3.000000 4.000000 3.000000 5.000000 4.000000 3.000000 4.000000 5.000000 9.000000 4.000000 9.000000 5.000000 9.000000 9.000000 9.000000 10.000000 10.000000 4.000000 10.000000 5.000000 10.000000 9.000000 10.000000 10.000000 11.000000 10.000000 15.000000 4.000000 15.000000 5.000000 15.000000 6.000000 16.000000 4.000000 16.000000 5.000000 16.000000 6.000000 Implement basic K-means algorithm to cluster the sample data set. Do not use built-in function such as kmeans for clustering. sample data set (kmtest ) provided. Make sure your program works with data set A. What to DO: 1. Clustering with K-means algorithm for kmtest dataset. a. Without normalization, cluster the dataset by choosing the K value as 2, 3, 4, 5. Plot results for each K values by showing each cluster with different color and cluster centers. b. With normalization, cluster the dataset by choosing the values as 2, 3, 4, 5. You should create clustering centers and clustering input for normalized data. Use Z-score normalization as the normalization method. First normalize the data and apply clustering on the normalized data. Plot results for each K values by showing each cluster with different color and cluster centers.

I need the answer for both questions as soon as possible. please make sure your answer is clearly written. 2. If X has 10 members, how many members does P(X) have? How many proper subsets does X have? 3. Prove that for all real numbers x and integers n, [x] = n if and only if there exists €, 0 SE < 1, such that x+E = n.

Hypothesis Testing Practice 6 points possible (graded) 1. Suppose we now instead have 30000 participants in the treatment group and 31000 participants in the control group. As before, we base the null hypothesis on the breast cancer death rate observed in the control group, which is 0.00203, and define Y as the number of deaths in the treatment group. Given Hypothesis Testing Practice 6 points possible (graded) 1. Suppose we now instead have 30000 participants in the treatment group and 31000 participants in the control group. As before, we base the null hypothesis on the breast cancer death rate observed in the control group, which is 0.00203, and define Y as the number of deaths in the treatment group. Given that we now have different sized treatment and control groups, can we still model Y as a Poisson variable (approximated from a Binomial) and perform the same hypothesis test using Y as the test statistic? If so, what is the null hypothesis in terms of the parameter (of the Poisson model)? Yes, y can still be modeled as Poisson (X), and the null hypothesis will be Ho: λ = 60.9 Yes, y can still be modeled as Poisson (X), and the null hypothesis will remain Ho : A = 63 No 2. Recall that we have the model X₁,..., X31000~ Bernoulli() for the outcomes for each patient in the treatment group. We wish to distinguish between Ho: = 0.00203 and HA < 0.00203 using the test statistic T. How does T distinguish between Ho and HA? If T is large, then the data is more compatible to Ho, and if T is small, especially much smaller than 0.00203 31000, then the data is compatible to HA. If T is small, then the data is more compatible to Ho, and if T is large, especially much larger than 0.00203 31000, then the data is compatible to HA. If T' is exactly equal to 0.00203 31000, then the data is compatible to Ho. Otherwise, the data is compatible to HA.

From the table below, calculate the actual distance for each point given the multiplying and additive constants equivalent to 98.5 and 0.62, respectively. Point Top stadia Middle stadia Below stadia Distance a) А 3 2 1 b) B 2.95 2.05 0.25 c) с 3.35 2.35 0.95 d) D 2.98 2.28 0.48 ) e) E 2.56 1.76 0.76

The v–t graph for the motion of a car as it moves along a straight road is shown. Draw the s–t and a–t graphs. Also determine the average speed and the distance traveled for the 15-s time interval. When t = 0, s = 0. v (m/s) 15 u = 0.6t2 t (s) 15

determine the time during which the datellite is above the horizon for an observer located at the north pole The periodic time of an earth satellite in a circular polar orbit is 116 minutes. th N Horizon B A R = 3960 mi S Determine the time during which the satellite is above the horizon for an observer located at the north pole. The time is 29 min.

Sporting Pro wants to prepare interim financial statements for the first quarter of 2020 but would like to avoid making a physical count of inventory. During the last five years, the company's gross profit rate has averaged 26%. The following information for the year's first quarter is available from its records: January 1 beginning inventory Purchases Purchase returns Transportation in Sales Sales returns $ 255,260 900,200 12,150 6,000 1,101,150 9,000 Required: Use the gross profit method to prepare an estimate of the company's March 31 inventory. SPORTING PRO Estimated Inventory March 31, 2020 Goods available for sale: Goods available for sale Estimated cost of goods sold: