Use Excel to simulate a normal distribution with a mean of 700 and a standard deviation of 5.
use excel generate a random sample of 1300 data points. Create a histogram where the first bin starts at 686.25 and the width of each bin is 2.5. You can have your last bin be 711.25. post your histogram
Use Excel to simulate a normal distribution with a mean of 700 and a standard deviation...
Use Excel to simulate a normal distribution with a mean of 700 and a standard deviation of 5 In Excel generate a random sample of 290 data points. Create a histogram where the first bin starts at 686.25 and the width of each bin is 2.5. You can have your last bin be 711.25. Save that histogram
Use Excel to simulate a normal distribution with a mean of 700 and a standard deviation of 5. First, generate a random sample of 50 data points. Create a histogram where the first bin starts at 686.25 and the width of each bin is 2.5. You can have your last bin be 711.25. Save that histogram as an image file and attach it here.
use Excel to simulate a normal distribution with a mean of 700 and a standard deviation of 5. generate a random sample of 150 data points in excel. Create a histogram where the first bin starts at 686.25 and the width of each bin is 2.5. You can have your last bin be 711.25. Save that histogram as an image file and attach it here using the Insert Image option.
We will be using Excel to simulate a normal distribution with a mean of 500 and a standard deviation of 9. Please note there are five parts to this question. First, generate a random sample of 50 data points. 1. Create a histogram where the first bin starts at 475.25 and the width of each bin is 4.5. You can have your last bin be 520.25. Save that histogram as an image file and attach it here using the Insert...
Use Excel to standard normal observations with assumed population parameters with mean 16 and standard deviation 5. Go to Data Analysis (you need to have chosen "Analysis Toolpack" first) -> Random Number Generation -> Normal. Generate one random variable with numbers generated for samples of size 5, 16, and 25 from the default standard normal distribution. This will simulate the importance of the "assume normal" assumption. Use the =) provided from the parent population as your "assumed" population standard deviation....
Then. generate a random sample of 1300 data points. Create a histogram where the first bin starts at 222.5 and the width of each bin is 5. You can have your that histogram as an image file and attach it here using the insert image option.
Please answer both 1 & 2. 1. Use Excel to generate 100 observations from the standard Normal distribution. a.Make a histogram of these observations. How does the shape of this histogram compare with a Normal density curve? 2. Use Excel to generate 100 Normally distributed random values (that is 100 outcomes of a Normally distributed random variable with mean 10 and standard deviation of 5). a. Make a histogram for your data. How does the shape of this histogram compare...
Please use html format! II. The goal of this problem is to simulate the distribution of the sample mean. We will use the buit load the dataset and avoid some problems, copy and paste the following command in dataset 1ynx. To lynx as.numeric(lynx) Assume this vector represents the population. Le, the mean of this vector is our "true mean" (a) Draw a histogram of the population, find the "true" mean, and the true" variance. Does this data look normally distributed?...
generate a random sample of 130 data points. Create a histogram where the first bin starts at 222.5 and the width of each bin is 5. You can have your last bin be 272.5 Save that histogram as an image file and attach it here using the Insert Image option
pick a number for mean and standard deviation generate 5 random numbers using a normal distribution and mean and standard deviation from (i) using your 5 numbers find the mean and the standard deviation of your data How far is your sample mean from your true mean? By 'far' I mean how many sample standard deviations. use the absolute value of distance here Repeat steps 2-4 1000 times. you should now have 1000 measures how far your sample mean is...