TNA Essays

TNA Essays TNA Essay TNA Essay TNA Introduction TNA is a process of gathering and interpreting data for identifying performance problems and suggesting solutions. ?Training needs analysis is a critical part of the training process. The TNA objective is twofold: to collect and evaluate information in order to find out what is being done now and what should be done now and later. We have no set procedure for performing a TNA, but the activities fall into three Stages (surveillance, investigation, analysis) and end with a report. The TNA concept provokes some problems within the organization, and the person sponsoring a TNA must cope with these.? (Smith Delahaye, 1998 p. 79) The fictive case scenario presented in this assignment will take place at The Slabrock Nightclub in Skien, Norway, where I actually used to work as the security manager. Some trendy nightclubs in Skien have been forced to close its doors because of failing to control crime on the premises. As a well-repudiated security consultant, I get a call from Slabrock Nightclub which have received multiple warning letters from the local authorities, threatening to revoke the club?s liquor license and operating permit. The conclusion from this call is that I am to conduct a TNA, write a report tna, bouncers, club, analysis, security, police, should, training, job, data, out, manager, management, investigation, clubs, smith, surveillance, slabrock, nightclub, need, call, being, performance, 1998, work, three, someone, serious, required, reports, plans/policies, person, patrons, organization, local

Difference Between Independent and Dependent Variables

Difference Between Independent and Dependent Variables The two main variables in an experiment are the independent and dependent variable. An independent variable is the variable that is changed or controlled in a scientific experiment to test the effects on the dependent variable. A dependent variable is the variable being tested and measured  in a scientific experiment. The dependent variable is dependent on the independent variable. As the experimenter changes the independent variable, the effect on the dependent variable is observed and recorded. Independent and Dependent Variable Example For example, a scientist wants to see if the brightness of light has any effect on a moth being attracted to the light. The brightness of the light  is controlled by the scientist. This would be the independent variable. How the moth reacts to the different light levels (distance to light source)  would be the dependent variable. How to Tell the Variables Apart The independent and dependent variables may be viewed in terms of cause and effect. If the independent variable is changed, then an effect is seen in the dependent variable. Remember, the values of both variables may change in an experiment and are recorded. The difference is that the value of the independent variable is controlled by the experimenter, while the value of the dependent variable only changes in response to the independent variable. Remembering Variables With DRYMIX When results are plotted in graphs, the convention is to use the independent variable as the x-axis and the dependent variable as the y-axis. The DRY MIX acronym can help keep the variables straight: D is the dependent variableR is the responding variableY is the axis on which the dependent or responding variable is graphed (the vertical axis) M is the manipulated variable or the one that is changed in an experimentI is the independent variableX is the axis on which the independent or manipulated variable is graphed (the horizontal axis) Independent vs Dependent Variable Key Takeaways The independent and dependent variables are the two key variables in a science experiment.The independent variable is the one the experimenter controls. The dependent variable is the variable that changes in response to the independent variable.The two variables may be related by cause and effect. If the independent variable changes, then the dependent variable is affected. Sources Carlson, Robert. A concrete introduction to real analysis. CRC Press, 2006. p.183.Dodge, Y. (2003) The Oxford Dictionary of Statistical Terms, OUP. ISBN 0-19-920613-9Everitt, B. S. (2002). The Cambridge Dictionary of Statistics (2nd ed.). Cambridge UP. ISBN 0-521-81099-X.