HRM 2420 Study Notes PDF

HRM 2420 C - 7:00 pm - 10:00 pm - ACW (Accolade West Building), Room 206. How to Answer a Short-Essay Question Effectively: 3.1 For each key point in your answers to an exam question, you should explain it with at least 40 words (3 to 4 lines). For example, if I ask you to discuss the main differe...

HRM 2420 C - 7:00 pm - 10:00 pm - ACW (Accolade West Building), Room 206. How to Answer a Short-Essay Question Effectively: 3.1 For each key point in your answers to an exam question, you should explain it with at least 40 words (3 to 4 lines). For example, if I ask you to discuss the main differences between two concepts, each concept is considered a key point. If I ask you to discuss a process, each step of the process is considered a key point. Chp 1 Population: group representing all members of a certain category Ex. York U Students vs. Sample: subset drawn from the population Parameter: fixed numerical values for populations vs. Statistic: estimate parameters using sample data Variables of measurement: anything that has more than a single value (age) -​ Quantitative or qualitative variables vs. Scales of measurement: Some items/questions used for measuring variables. -​ Nominal: categories (gender, blood type) -​ Ordinal: ranked -​ Interval: values are ordered w/ equal distance -​ Ratio: values ordered, distance between values are equal, can include zero (0-20%) Quasi-experimental research design: outside the lab, in a naturally occurring setting (more difficult to control conditions than experimental design) vs. Correlational research design: Collecting data on variables & conducting analyses to determine relationship strength. Distribution: collection of data on a variable that can be arranged in order and presented graphically Benchmarking: comparing a business’s operations w/ other competitors Sample Methods Random Sampling: every member of the population has = chance of being selected Representative Sampling: cases are intentionally chosen to match the larger population based on specific characteristics. Convenience Sampling: chosen based on their proximity, ease of access, and willingness to participate. Big data: large in volume, variety, and velocity. 3 Types of HR Analytics: Descriptive (analyses historical data to understand a period of time), predictive (uses statistical models/ forecast to predict future based on current & historical data), prescriptive (provides recommendations by analysing potential outcomes) HR Analytics used for key HRM functions: -​ analyse/ design jobs -​ Manage diversity -​ Recruit, select, train individuals -​ Reward, compensate -​ Manage employees exit from organisation etc. Chp 2 Central tendency: central position within a set of data 3 Types: -​ Mean: average of a distribution of scores -​ Median: located in middle (useful when scores are skewed: negatively skewed to the left, positively skewed to the right or normal/ no skew) -​ Mode: which score occurs most frequently (can have no, 1 or more than 1 mode, provides least info) Variability: the spread of scores within a set of data Types: -​ Range: difference between largest and smallest score (can be misleading) -​ Interquartile range (IQR): difference between score that marks 75th and 25th percentile -​ Variance: average of amount of dispersion in a distribution of scores -​ Standard Deviation: square root of variance (most useful to measure average dispersion of scores in distribution) Histograms: display the frequency of data within certain ranges. Box plots: show the distribution of data using the five-number summary, useful when comparing between multiple datasets. 1.​ Scenario 1: Suppose that you have collected data from a random sample of 10 adults and want to know how much time each of them spends working outside the home in a week. You get the following data: 40 50 40 30 0 35 25 45 5 40 Please answer the following questions using these data: 1.1 What is the mode of this distribution? 1.2 What is the median of this distribution? 1.3 What is the mean of this distribution? 1.4 Do you believe this distribution is skewed in one direction or another? Why do you think so?  1.5 What is the range of this distribution? Chp 3 The confidence interval: provides a range of values that researchers are confident, to a certain degree of probability, contains the population parameter Statistical significance: make inferences about population from which sample were selected Descriptive statistics: measures of central tendency & variability Ie. mean, median, mode, range, variance & standard deviation *scores with the alpha levels p