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Homework #1 SOCY 3115 Spring 20 Read the Syllabus and FAQ on how to do your homework before beginning the assignment! To get consideration for full credit, you must: · Follow directions; · Show all work required to arrive at answer (statistical calculations often require multiple steps, so you need to write these down, not just skip to the final answer) · Use appropriate statistical notation at all times (e.g. if you are calculating a population mean, begin with the equation for population mean) · Use units in your answer, where appropriate (e.g. a mean time would be “6.5 hours” rather than just “6.5”) Understanding the Structure of Data 1. For the following rectangular dataset: Id Highest degree Works full-time Annual income cat 1 Did not grad HS Yes Low 2 HS dip Yes Low 3 HS dip No Med 4 BA No Low 5 BA Yes Med 6 MA Yes High 7 HS dip Yes Med a. What is the unit-of-analysis of the dataset? b. How many variables are in the dataset? c. How many observations/cases are in the dataset? d. For eachvariable that is not named “id”: i. What is the variable name? ii. What is the level-of-measurement? iii. What are the values for the variable? iv. If you had to make a guess, what do you think the “question” was that was asked of the unit-of-analysis to get these data? (for example, if we had a continuous variable called “num_pets” the question might be “How many pets live in your household?”) 2. For the following rectangular dataset: Id num_bdrms num_bthrms sqft Ranch 1 4 3 3200 Yes 2 2 1.5 2800 Yes 3 2 1 1200 Yes 4 3 2 1500 No 5 2 2 1100 No a. What is the unit-of-analysis of the dataset? b. How many variables are in the dataset? c. How many observations/cases are in the dataset? d. For each variable that is not named “id”: i. What is the variable name? ii. What is the level-of-measurement? Before answering, be sure to consult the slide called “Level of measurement – language to use”. Use the formal language! iii. What are the values for the variable? iv. If you had to make a guess, what do you think the “question” was that was asked of the unit-of-analysis to get these data? (for example, if we had a continuous variable called “num_pets” the question might be “How many pets live in your household?”) 3. For each of the following questions (1) construct a dataset with one variable and three observations (2) add data that could have theoretically been collected (just make up the actual responses to the question); and (3) indicate the level-of-measurement of the variable. I’ve done two examples for you. Example#1: What is your current age? (individual is the unit-of-analysis) idage 1 25 2 32 3 61 The age variable is continuous/interval ratio. Example#2: What is the size of this hospital based on number of beds? (hospital is the unit-of-analysis)? Answers can be small (1-100 beds), medium (101-500 beds), large (501 beds to 1000 beds), extra large (1001+ beds) idhosp_size 1 med 2 med 3 ext ...
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DESCRIPTIVE ANALYSIS 1 DESCRIPTIVE ANALYSIS 8 Examining Measurements of Central Tendencies Examining Measurements of Central Tendencies This discussion board is based on the measurement of central tendencies whereas the nominal, ordinal, interval and ratio allow researcher to analyze data. Each of these measurements provide researchers with the ability to measure sets of data that do not represent numerical values. Salkind (2017) defined a level measurement with an outcome that fit into one and only class or category as nominal. The level of measurement assigns value to a specific item than assign a value to the item based on the appeal to an individual. The nominal measurement that I chose was labor force status. The descriptive characteristics that were chosen for the completion of the data set were represented some form of employment. Salkind (2017) explained the ordinal measurement as the characteristic of the assigning order or ranking data. The ordinal measurement that I chose was a ranking of how individuals view their political affiliations. The characteristics were assigned a value which for the mean, median and mode to be determined. The sum of a data set divide by the number data points represents the mean (Salkind, 2017). The mean for a data set may be skewed based on extreme number contained in the set of number. By focusing on the median, Salkind (2017) defined as a true midpoint of the data set that does not take in consideration extreme number. The median produces a more conclusive number that is related to the true data without influences. When analyzing data, situations may occur where the data is repetitive. This repetition of the number in a data is known as the mode (Salkind, 2017). A data set may have multiple modes and may have greater determining factor mean and how the data is interpreted. Nominal Data The nominal data set for ‘Labor for status’ comprised of 10 descriptive terms that represents some phase of employment. The data were assigned numbers 0 to 9 based on the stage of employed (e.g. “working fulltime” =1). The data set consisted of 575 respondents of which only one data was missing. The data shows that nearly 60% of respondents reported that were “working fulltime”. The corresponding value associated with “working fulltime” was 1. The data show that most respondents are employed in some fashion calculating a mean of 2.57, median of 1 and a mode of 1. The median of 1 seems to be an anomaly in the data based on the data set range of nine. The standard deviation of 2.246 and variance of 5.044. Based on the information analyzed, 68% of the respondents are represented between .33 and 4.81. The variance shows the consistency of the data based on the distance from .33 to 4.81. Statistics Labor force status N Valid 574 Missing 1 Mean 2.57 Std. Error of Mean .094 Median 1.00 Mode 1 Std. Deviation 2.246 Variance 5.044 Skewness 1.088 Std. Error of Skewness .102 Kurtosis -.392 Std..
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DESCRIPTIVE ANALYSIS1DESCRIPTIVE ANALYSIS8Examining .docx
donaldp2
DESCRIPTIVE ANALYSIS 1 DESCRIPTIVE ANALYSIS 8 Examining Measurements of Central Tendencies Examining Measurements of Central Tendencies This discussion board is based on the measurement of central tendencies whereas the nominal, ordinal, interval and ratio allow researcher to analyze data. Each of these measurements provide researchers with the ability to measure sets of data that do not represent numerical values. Salkind (2017) defined a level measurement with an outcome that fit into one and only class or category as nominal. The level of measurement assigns value to a specific item than assign a value to the item based on the appeal to an individual. The nominal measurement that I chose was labor force status. The descriptive characteristics that were chosen for the completion of the data set were represented some form of employment. Salkind (2017) explained the ordinal measurement as the characteristic of the assigning order or ranking data. The ordinal measurement that I chose was a ranking of how individuals view their political affiliations. The characteristics were assigned a value which for the mean, median and mode to be determined. The sum of a data set divide by the number data points represents the mean (Salkind, 2017). The mean for a data set may be skewed based on extreme number contained in the set of number. By focusing on the median, Salkind (2017) defined as a true midpoint of the data set that does not take in consideration extreme number. The median produces a more conclusive number that is related to the true data without influences. When analyzing data, situations may occur where the data is repetitive. This repetition of the number in a data is known as the mode (Salkind, 2017). A data set may have multiple modes and may have greater determining factor mean and how the data is interpreted. Nominal Data The nominal data set for ‘Labor for status’ comprised of 10 descriptive terms that represents some phase of employment. The data were assigned numbers 0 to 9 based on the stage of employed (e.g. “working fulltime” =1). The data set consisted of 575 respondents of which only one data was missing. The data shows that nearly 60% of respondents reported that were “working fulltime”. The corresponding value associated with “working fulltime” was 1. The data show that most respondents are employed in some fashion calculating a mean of 2.57, median of 1 and a mode of 1. The median of 1 seems to be an anomaly in the data based on the data set range of nine. The standard deviation of 2.246 and variance of 5.044. Based on the information analyzed, 68% of the respondents are represented between .33 and 4.81. The variance shows the consistency of the data based on the distance from .33 to 4.81. Statistics Labor force status N Valid 574 Missing 1 Mean 2.57 Std. Error of Mean .094 Median 1.00 Mode 1 Std. Deviation 2.246 Variance 5.044 Skewness 1.088 Std. Error of Skewness .102 Kurtosis -.392 Std..
DESCRIPTIVE ANALYSIS1DESCRIPTIVE ANALYSIS8Examining .docx
DESCRIPTIVE ANALYSIS1DESCRIPTIVE ANALYSIS8Examining .docx
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DESCRIPTIVE ANALYSIS1DESCRIPTIVE ANALYSIS8Examining .docx
DESCRIPTIVE ANALYSIS1DESCRIPTIVE ANALYSIS8Examining .docx
DESCRIPTIVE ANALYSIS1DESCRIPTIVE ANALYSIS8Examining .docx
DESCRIPTIVE ANALYSIS1DESCRIPTIVE ANALYSIS8Examining .docx
Central tendency spread - symmetry (4.0)
Central tendency spread - symmetry (4.0)
Participants
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