Statistics in Data Collection and Analysis

Describe what you understand by ‘independent variable’ and ‘dependent variable’ in a scientific study? ( 5 points) An independent variable is something you have control over, what you can choose and manipulate. It is a variable that stands alone and doesn’t change by other variables. Although in some cases, you may not be able to manipulate the independent variable. It could be already there and or fixed. A dependent variable is the variable that’s being tested in an experiment. If the experimenter changes the independent variable, the change in the dependent variable is observed and recorded. For example a scientist is testing the effect of light and dark on the behavior of moths by turning a light on and off. The independent variable is the amount of light and the moth’s reaction is dependent variable. A change in the independent variable (amount of light) directly causes a change in the dependent variable (moth

a. For each year, create tables of counts of gender and of nationality. Then create column charts of

Quantitative data is facts that are written in numerical form and then proven. The way Quantitative data is recorded is in numbers. An example of Quantitative data is 55%take bus, 25% take train, 10% walk and 10% car.

3. Quantitative data is easily compiled into something meaningful because it is based on concrete data. On the other hand, qualitative data is presented in a raw form and needs

Dependent variables are ones that change due to the independent variable. Independent variables are variables that can be manipulated or measured. This influences the dependent variables.

To view the research on a nominal scale, the research data can be drawn from the type of class. The word nominal is derived from the root word in Latin for name (Usable Stats, 2013). The name of the class, Psychological Statistics, is the nominal measurement for this research. When conducting this study, the study will only be measured during the course of this specific class. The results could drastically change when considering another type of class such as Quantitative Literacy as the cognitive understanding of such a collegic math class may be more optimal through a different course-delivery format.

13. Distinguish between quantitative and qualitative data. Which type would be presented in a data

The information in the table below refers to the 2008 model year product line of BMW automobiles. Identify the Individuals, variables, and data corresponding to the variables in the table below. Determine whether each variable is qualitative, continuous, or, discrete. Please refer to problems #51 and #53 on page 13 for examples.

The given information is related to 30 major League Baseball teams for the 2012 season. Here, the sample size is large (n 230) but the population standard deviation (a) is unknown. So, apply one sample t confidence intervals. Find the 95% confidence interval for the mean number of home runs per team. Using MINITAB, following are the steps to obtain the 95% confidence intervals for the population mean. 1) Import the data into one column named as RUNS, 2) Choose Stat Basic Statistics 21-Sample t... 3) Select the Samples in columns option button, 4) Click in the Samples in columns text box and specify RUNS. 5) Click the Options...button, 6) Enter 95% in the confidence level text box. 7) Click the arrow button at the right of the Alternative drop-down list box and select not equal, 8) Click OK twice. output: One-Sample T Runs Variable 30 164.47 32.97 Mean StDev SE Mean 955 CI Runs 6.02 (152.15, 176.78) From the above output, the 95% confidence interval for the mean number of home runs per team is lies between 152.15 and 176.78

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Use the given degree of confidence and sample data to construct a confidence interval for the population proportion. 1) Of 346 items tested, 12 are found to be defective. Construct a 98% confidence interval for the percentage of all such items that are defective. A) (3.34%, 3.59%) B) (1.18%, 5.76%) C) (1.85%, 5.09%) D) (0.93%, 6.00%) E) (0.13%, 6.80%) 2) Of 81 adults selected randomly from one town, 64 have health insurance. Construct a 90% confidence interval for the percentage of all adults in the town who have health insurance. A) (71.6%, 86.5%) B) (67.4%, 90.7%) C) (70.1%, 87.9%) D)

This is information that is measured using numerical values and is very accurate as it is based on facts and is statistics. The information is presented as statistics and can be obtained from methods like questionnaires and surveys. Quantitative questions don’t allows the individual to give a subjective answer. NatWest this data to analyse for patterns and trends of their customers banking habits. This then allows them to make projects for the banks which would be influenced by the quantitative data they would have collected through a survey in there branches nationwide.

This is the initial part of the data analysis that many people don’t go beyond. While Kaushik has been praising the need to deliver “actionable insights”, one must first understand the basic data analysis prior to taking the next step.

The collected data will be analyzed using thematic data analysis. The data analysis process will be to organize, code, categorize, and interpret. Each interview transcript, observation field note, and police or school record will be uploaded into Atlas.ti in order to store and manage the data, and later will be used to code and categorize. Organizing and memoing the data are significant steps because they encompass reading through, sorting, familiarizing with the material, making initial codes, and, more generally, comprehending the collected data in order to create a “detailed description of the case” (Creswell 2013, p. 101). The description will be thorough, in-depth, and will contextualize the case in the unique setting of the South Bronx, thereby serving as a validation strategy (Alley 2016). The description serves to depict the complexity of the case itself and allows the data to be analyzed sequentially based on the actual progression of the case. The next step is to identify emerging patterns, themes, similarities, and differences using categorical aggregation (Creswell, 2013). The themes and patterns will be directly interpreted to “develop naturalistic generalizations of what was “learned”” (Creswell 2013, p. 190). Direct interpretation is a unique method for the case study approach because it focuses on the information made explicit through the research and does not “generalize beyond the case” (p. 101). Ultimately, the objective is to distill

Annex A Basic Analysis | | Reciprocating | Scroll | All | Average Price | Europe | $ 31,31 | $ 38,60 | $ 32,28 |   | Latin | $ 38,71 | Does not exist | $ 38,71 |   | North | $ 32,43 | $ 34,69 | $ 33,11 |   | Total | $ 33,73 | $ 35,67 | $ 34,08 | Average Volume | Europe | 111.307,69 | 88.000,00 | 108.200,00 |   | Latin | 67.000,00 | Does not exist | 67.000,00 |   | North | 121.142,86 | 174.500,00 | 137.150,00 |   | Total | 103.054,05 | 152.875,00 | 111.911,11 | Average BTU | Europe | 410,00 | 850,00 | 468,67 |   | Latin |

It has been a joy to do some research on AIU below you see the percentage of male and females that are with in AIU, the tenure these employees have been with the