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MAT 202 Belhaven University Quantitative Reasoning Questions
Question 1Excel Assignment 3: StatisticsMicrosoft Excel has numerous built-in functions for descriptive statistics as well ...
MAT 202 Belhaven University Quantitative Reasoning Questions
Question 1Excel Assignment 3: StatisticsMicrosoft Excel has numerous built-in functions for descriptive statistics as well as probability distributions like the Normal Distribution.1. Average(value1, value2), Quartile.Inc(value1, value2, value 3), Median(value1, value2), Min(value1, value2), Max(value1, value2), StDev.S(value1, value2)Many descriptive stats functions work in a similar way to the Count and Sum functions. The Average, Median, Min, Max, and StDev.S functions gives the mean, median, minimum value, maximum value, and sample standard deviation respectively between value1 and value2. The Quartile.Inc function gives the quartile number value3 (with value3 being between 1 and 4) between value1 and value2.2. To find probabilities (or percentiles) with the Normal Distribution, let us use a for the mean and b for the standard deviation. Then Norm.Dist(k, a, b, True) gives the probability that a randomly selected value, x, is less than (or less than or equal to) k.That means, using the law of complements, that finding the probability that x is greater than (or greater than or equal to) k is 1 – Norm.Dist(k, a, b, True).Exercises: Open a new spreadsheet in Microsoft Excel and complete the following.1. Type the following words in given cells. Cell WordB1 ValueC1 StatsC2 CountC3 SumC4 MeanC5 MinC6 Q1Cell WordC7 MedianC8 Q3C9 MaxC10 Standard Dev. G1 Normal Dist Q F2 MeanF3 Standard Dev. 2. In cell A2, type “=RandBetween(1,10)”, and drag this formula from A2 down to A26. You have now created 25 random numbers between 1 and 10.3. THIS IS IMPORTANT. The problem with RandBetween is that it will generate a new set of values every time the user performs a new calculation. To keep the values we h ave, highlight cells A2 to A26 (hold down the SHIFT key and tap the DOWN button to do so). Copy these values. In cell B2, right click the mouse and select PASTE VALUES. Now the values in the B column will stay the way we want them.MAT 202 Quantitative Reasoning4. In cell D2, type “=COUNT(B2:B26)”, and in cell D3, type “=Sum(B2:B26)” to get the count and sum of the values in our data set.5. In a similar way, in D4, type “=Average(B2:B26)” to calculate the mean. In D5, type “=Min(B2:B26)” and in D9, type “=Max(B2:B26)” to calculate the minimum and maximum values in our data set.6. To find the median, in D7, type “=Median(B2:B26)”, and in D6 and D8, type “=Quartile.Inc(B2:B26, 1)” and “=Quartile.Inc(B2:B26,3)” to find the first and third quartiles respectively. Note, we could also use “=Quartile.Inc(B2:B26, 2)” to the find the median.In the future, that may be a faster method, as we could drag the formula down the B column to find our quartiles.7. In cell D10, find the sample standard deviation by “=StDev.S(B2:B26)”. If you need the population standard deviation (only needed if our sample size is larger than about 30), use “=StDev.P(value1, value2).Normal Distribution Exercises: Suppose heights of lavender plants are normally distributed with a height of 21” and a standard deviation of 4”. Suppose that you select a lavender plant (randomly) in your garden.In cells G2 and G3, type “21” and “4” respectively.1. What’s the probability that your selected lavender plant has a height of 22” or less? In cell F5, type “P(x leq 22)”, and in cel l G5 calculate this probability.We can calculate this by typing “=Norm.Dist(22, G2, G3, True)” to get the value 0.598706326.2. What’s the probability that your selected lavender plant has a height greater than 22”? In cell F6, type “P(x > 22)”, and in cell G6 calculate this probability.We can calculate this by typing “=1 - Norm.Dist(22, G2, G3, True)” to get the value 0.401293674.3. What’s the probability that your selected lavender plant has a height greater than 14”? In cell F7, type “P(x > 14)”, and in cell G7 calculate this probability.We can calculate this by typing “=1 - Norm.Dist(14, G2, G3, True)” to get the value 0.959940843.MAT 202 Quantitative Reasoning8. Save and submit your spreadsheet in Canvas under Excel Assignment 2Question 2Prompt: We have talked about the importance of having a representative sample. Explain how it could be misleading and even dangerous to not have a good sample for a statistic test.Requirements: 250 words minimum initial post, 100 words minimum replyQuestion 3Prompt: Find an example of descriptive statistics and an example of inferential statistics common to everyday life.Requirements: 250 words minimum initial post, 100 words minimum replyQuestion 2
chapter 12 review test 4th grade hw
I need this done for my 4th grader. please write clearly to transpose information thanks. Problems 1-22 preferred if type ...
chapter 12 review test 4th grade hw
I need this done for my 4th grader. please write clearly to transpose information thanks. Problems 1-22 preferred if typed however clear typing will do thanks again
SOCI 332 APUS Test of Significance Job Satisfaction Paper
In Week 4, we used epsilons and 10-percent-point rule to determine if a potential relationship between two variables is wo ...
SOCI 332 APUS Test of Significance Job Satisfaction Paper
In Week 4, we used epsilons and 10-percent-point rule to determine if a potential relationship between two variables is worth examining further. During Week 5, we studied tests of significance. In this week's discussion, we will apply these tests of significance to our project variables. We will also run measures of association to determine the strength and direction of the relationship between our variables. As we discussed previously, the levels of measurement of our variables determine which test of significance works for the research project. Here is the guideline: 1. Before-and-after design and the DV is at I/R level: Dependent Sample T-test2. DV and IV are BOTH categorical variables (nominal/ordinal): Chi-square*Special note for Chi-square: you should have less than 20% of the cells with an expected count of 5 or less. This information is reported automatically, right below the chi-square output table. If your chi-square test fails to meet this requirement, it is necessary to use "recoding" to combining certain answer categories together so the expected counts would increase. 3. DV and IV are both continuous (interval/ratio) variables: regression4. Comparison of groups (when IV is categorical - nominal/ordinal and DV is continuous - interval/ratio): a. Between 2 groups: Independent Sample T-test b. Among 3 or more groups: ANOVAWhy do we need to run tests of significance?They allow us to see if our relationship is "statistically significant." To be more specific, these tests tell us if a relationship observed in a sample, like your research project based on GSS 2016 data set, is generalizable to the population from which this sample was drawn (US adults).Test results reported under "p" in the SPSS output tells us the chances that a relationship observed in the sample is not real, but rather due to factors like a sampling error. We compare this "chance" with level of significance, commonly set as .05 or .01. If this chance is smaller than level of significance, we can reject the null hypothesis, and keep the research hypothesis.Next, we'll use tests of "measures of association" to figure out the exact strength of a relationship between two variables. In addition, we'll learn how to interpret SPSS outputs for measures of association tests such as lambda, gamma, and Pearson's r, along with other possible tests. These tests are also specific to the level of measurement of your variables. Here are the guidelines:Both DV and IV are nominal variables: Lambda (when it is not a 2X2 table)If it is a 2X2 table: PhiBoth DV and IV are ordinal variables: GammaOne variable ordinal AND the other variable dichotomous nominal (like Yes/No, male/female, etc.): GammaOne variable ordinal AND the other variable nominal (not dichotomous, has more than 2 categories): Cramer's V.Both DV and IV are I/R variables: Pearson's rTo interpret the output, see attached handout. Keep in mind measures of association is a statistical procedure based on Proportional Reduction of Error (PRE). Thus the format of interpretation will be: Knowing the IV will reduce error in predicting the DV by *%. Please note: Don't just say "IV" and "DV" in your explanation. You need to enter your variables names for IV and DV, and replace * for the exact test value from the output. If the value of Lambda is .34, then it will be interpreted as 34%.****Ok, now it is time for you to try! For this week's discussion, be sure to perform the correct test of significance (choose one) and measure of association (choose one) on your variables for the final project. You can download the class handout attached at the bottom of the page.This week in the discussion:I. You will decide which test of significance you will use for your project. Use the guideline above to make your choice.II. You will use the process for hypothesis testing which outlines five steps:Write your research hypothesis (H1) and your null hypothesis (H0).Identify and record your level of significance (alpha): either .05 or .01.Complete the significance test using SPSS. (Include the output of the analysis (table) in your post.)Identify the number under Sig. (2-tail). This will be represented by "p." Compare the numbers in steps 2 (alpha) and 4 (p) and apply the following rule:If p < or = alpha, than you reject the null hypothesisDetermine what to do with your null and explain this to your reader. Be sure to go beyond the phrase "reject or fail to reject the null" and explain what that means to your research.III. You will decide which measure of association you will use for your project. Use the guideline above to make your choice. Include the output (table) in your post. Based on the output, describe the strength and direction of the relationship between the variables. Also explain the PRE.**** I have attached information about my variables "satjob1 and happy". the gss 2018 spreadsheet that contains both my variables and a helpful handout from class.
3 pages
R Coding In Optimzation
Craft Studio Furnishings (CSF) produces a unique line of cane furniture. The items currently on the market are table chair ...
R Coding In Optimzation
Craft Studio Furnishings (CSF) produces a unique line of cane furniture. The items currently on the market are table chairs, easy chairs, and love ...
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MAT 202 Belhaven University Quantitative Reasoning Questions
Question 1Excel Assignment 3: StatisticsMicrosoft Excel has numerous built-in functions for descriptive statistics as well ...
MAT 202 Belhaven University Quantitative Reasoning Questions
Question 1Excel Assignment 3: StatisticsMicrosoft Excel has numerous built-in functions for descriptive statistics as well as probability distributions like the Normal Distribution.1. Average(value1, value2), Quartile.Inc(value1, value2, value 3), Median(value1, value2), Min(value1, value2), Max(value1, value2), StDev.S(value1, value2)Many descriptive stats functions work in a similar way to the Count and Sum functions. The Average, Median, Min, Max, and StDev.S functions gives the mean, median, minimum value, maximum value, and sample standard deviation respectively between value1 and value2. The Quartile.Inc function gives the quartile number value3 (with value3 being between 1 and 4) between value1 and value2.2. To find probabilities (or percentiles) with the Normal Distribution, let us use a for the mean and b for the standard deviation. Then Norm.Dist(k, a, b, True) gives the probability that a randomly selected value, x, is less than (or less than or equal to) k.That means, using the law of complements, that finding the probability that x is greater than (or greater than or equal to) k is 1 – Norm.Dist(k, a, b, True).Exercises: Open a new spreadsheet in Microsoft Excel and complete the following.1. Type the following words in given cells. Cell WordB1 ValueC1 StatsC2 CountC3 SumC4 MeanC5 MinC6 Q1Cell WordC7 MedianC8 Q3C9 MaxC10 Standard Dev. G1 Normal Dist Q F2 MeanF3 Standard Dev. 2. In cell A2, type “=RandBetween(1,10)”, and drag this formula from A2 down to A26. You have now created 25 random numbers between 1 and 10.3. THIS IS IMPORTANT. The problem with RandBetween is that it will generate a new set of values every time the user performs a new calculation. To keep the values we h ave, highlight cells A2 to A26 (hold down the SHIFT key and tap the DOWN button to do so). Copy these values. In cell B2, right click the mouse and select PASTE VALUES. Now the values in the B column will stay the way we want them.MAT 202 Quantitative Reasoning4. In cell D2, type “=COUNT(B2:B26)”, and in cell D3, type “=Sum(B2:B26)” to get the count and sum of the values in our data set.5. In a similar way, in D4, type “=Average(B2:B26)” to calculate the mean. In D5, type “=Min(B2:B26)” and in D9, type “=Max(B2:B26)” to calculate the minimum and maximum values in our data set.6. To find the median, in D7, type “=Median(B2:B26)”, and in D6 and D8, type “=Quartile.Inc(B2:B26, 1)” and “=Quartile.Inc(B2:B26,3)” to find the first and third quartiles respectively. Note, we could also use “=Quartile.Inc(B2:B26, 2)” to the find the median.In the future, that may be a faster method, as we could drag the formula down the B column to find our quartiles.7. In cell D10, find the sample standard deviation by “=StDev.S(B2:B26)”. If you need the population standard deviation (only needed if our sample size is larger than about 30), use “=StDev.P(value1, value2).Normal Distribution Exercises: Suppose heights of lavender plants are normally distributed with a height of 21” and a standard deviation of 4”. Suppose that you select a lavender plant (randomly) in your garden.In cells G2 and G3, type “21” and “4” respectively.1. What’s the probability that your selected lavender plant has a height of 22” or less? In cell F5, type “P(x leq 22)”, and in cel l G5 calculate this probability.We can calculate this by typing “=Norm.Dist(22, G2, G3, True)” to get the value 0.598706326.2. What’s the probability that your selected lavender plant has a height greater than 22”? In cell F6, type “P(x > 22)”, and in cell G6 calculate this probability.We can calculate this by typing “=1 - Norm.Dist(22, G2, G3, True)” to get the value 0.401293674.3. What’s the probability that your selected lavender plant has a height greater than 14”? In cell F7, type “P(x > 14)”, and in cell G7 calculate this probability.We can calculate this by typing “=1 - Norm.Dist(14, G2, G3, True)” to get the value 0.959940843.MAT 202 Quantitative Reasoning8. Save and submit your spreadsheet in Canvas under Excel Assignment 2Question 2Prompt: We have talked about the importance of having a representative sample. Explain how it could be misleading and even dangerous to not have a good sample for a statistic test.Requirements: 250 words minimum initial post, 100 words minimum replyQuestion 3Prompt: Find an example of descriptive statistics and an example of inferential statistics common to everyday life.Requirements: 250 words minimum initial post, 100 words minimum replyQuestion 2
chapter 12 review test 4th grade hw
I need this done for my 4th grader. please write clearly to transpose information thanks. Problems 1-22 preferred if type ...
chapter 12 review test 4th grade hw
I need this done for my 4th grader. please write clearly to transpose information thanks. Problems 1-22 preferred if typed however clear typing will do thanks again
SOCI 332 APUS Test of Significance Job Satisfaction Paper
In Week 4, we used epsilons and 10-percent-point rule to determine if a potential relationship between two variables is wo ...
SOCI 332 APUS Test of Significance Job Satisfaction Paper
In Week 4, we used epsilons and 10-percent-point rule to determine if a potential relationship between two variables is worth examining further. During Week 5, we studied tests of significance. In this week's discussion, we will apply these tests of significance to our project variables. We will also run measures of association to determine the strength and direction of the relationship between our variables. As we discussed previously, the levels of measurement of our variables determine which test of significance works for the research project. Here is the guideline: 1. Before-and-after design and the DV is at I/R level: Dependent Sample T-test2. DV and IV are BOTH categorical variables (nominal/ordinal): Chi-square*Special note for Chi-square: you should have less than 20% of the cells with an expected count of 5 or less. This information is reported automatically, right below the chi-square output table. If your chi-square test fails to meet this requirement, it is necessary to use "recoding" to combining certain answer categories together so the expected counts would increase. 3. DV and IV are both continuous (interval/ratio) variables: regression4. Comparison of groups (when IV is categorical - nominal/ordinal and DV is continuous - interval/ratio): a. Between 2 groups: Independent Sample T-test b. Among 3 or more groups: ANOVAWhy do we need to run tests of significance?They allow us to see if our relationship is "statistically significant." To be more specific, these tests tell us if a relationship observed in a sample, like your research project based on GSS 2016 data set, is generalizable to the population from which this sample was drawn (US adults).Test results reported under "p" in the SPSS output tells us the chances that a relationship observed in the sample is not real, but rather due to factors like a sampling error. We compare this "chance" with level of significance, commonly set as .05 or .01. If this chance is smaller than level of significance, we can reject the null hypothesis, and keep the research hypothesis.Next, we'll use tests of "measures of association" to figure out the exact strength of a relationship between two variables. In addition, we'll learn how to interpret SPSS outputs for measures of association tests such as lambda, gamma, and Pearson's r, along with other possible tests. These tests are also specific to the level of measurement of your variables. Here are the guidelines:Both DV and IV are nominal variables: Lambda (when it is not a 2X2 table)If it is a 2X2 table: PhiBoth DV and IV are ordinal variables: GammaOne variable ordinal AND the other variable dichotomous nominal (like Yes/No, male/female, etc.): GammaOne variable ordinal AND the other variable nominal (not dichotomous, has more than 2 categories): Cramer's V.Both DV and IV are I/R variables: Pearson's rTo interpret the output, see attached handout. Keep in mind measures of association is a statistical procedure based on Proportional Reduction of Error (PRE). Thus the format of interpretation will be: Knowing the IV will reduce error in predicting the DV by *%. Please note: Don't just say "IV" and "DV" in your explanation. You need to enter your variables names for IV and DV, and replace * for the exact test value from the output. If the value of Lambda is .34, then it will be interpreted as 34%.****Ok, now it is time for you to try! For this week's discussion, be sure to perform the correct test of significance (choose one) and measure of association (choose one) on your variables for the final project. You can download the class handout attached at the bottom of the page.This week in the discussion:I. You will decide which test of significance you will use for your project. Use the guideline above to make your choice.II. You will use the process for hypothesis testing which outlines five steps:Write your research hypothesis (H1) and your null hypothesis (H0).Identify and record your level of significance (alpha): either .05 or .01.Complete the significance test using SPSS. (Include the output of the analysis (table) in your post.)Identify the number under Sig. (2-tail). This will be represented by "p." Compare the numbers in steps 2 (alpha) and 4 (p) and apply the following rule:If p < or = alpha, than you reject the null hypothesisDetermine what to do with your null and explain this to your reader. Be sure to go beyond the phrase "reject or fail to reject the null" and explain what that means to your research.III. You will decide which measure of association you will use for your project. Use the guideline above to make your choice. Include the output (table) in your post. Based on the output, describe the strength and direction of the relationship between the variables. Also explain the PRE.**** I have attached information about my variables "satjob1 and happy". the gss 2018 spreadsheet that contains both my variables and a helpful handout from class.
3 pages
R Coding In Optimzation
Craft Studio Furnishings (CSF) produces a unique line of cane furniture. The items currently on the market are table chair ...
R Coding In Optimzation
Craft Studio Furnishings (CSF) produces a unique line of cane furniture. The items currently on the market are table chairs, easy chairs, and love ...
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