Reference no: EM132359296

Research Methods and Statistics in Exercise and Sport Assignment -

Overview - For Assignment you are required to provide responses to the questions below. There are 9 questions (5 questions in Part A, 4 questions in Part B).

Part A - Questions to be answered

Q1. What are the differences between quantitative and qualitative research methods in terms of;

i. the types of research questions posed,

ii. the common methods used for each approach,

iii. the forms of information (data) that are gathered.

Q2. A skill acquisition researcher is interested in examining the effects of practice variability on learning of golf skills. She aims to set up an experiment in her laboratory where she will examine the effects of different practice schedules on a simulated putting skills test. She proposes to have a total of 90 participants who will be randomly assigned into one of three practice schedules. One group (n = 30) will complete the practice trials according to a constant practice schedule [CP group] where they will complete the 40 practice trials of the putting skill from a distance of 3 meters. Another group (n = 30) will complete the practice trials according to a variable practice schedule [VP group] where they complete 40 practice trials of the putting skill from four different distances (10 trials at each of 1, 3, 5 and 7 meter distances) in a random order. A third group (n = 30) will not complete any practice trials - effectively a no practice schedule [NP group]. Performance will be determined using a putting skill test (10 putts) over a distance of 4 meters after participants have completed the practice trials as per their group schedule. Each putt is scored using a target grid with concentric circles marked where 10 = 'ball enters the hole (successful putt)'; 9 = 'close to the hole' and so on through to 0 = 'ball fails to land within bounds of target grid'. The researcher aims to ensure that conditions (e.g., temperature, lighting, noise) during the experiment will be carefully controlled.

For the experiment described, identify the following (make sure you number your responses to each of the separate questions):

i. What is the independent variable?

ii. What is the dependent variable?

iii. How many levels of the independent variable are there?

iv. What type of measure is the independent variable (i.e., what measurement scale)?

v. What is the null hypothesis for the experiment (i.e., state the null hypothesis)?

vi. What is the alternative hypothesis for the experiment (i.e., state the alternative hypothesis)?

Q3. Thinking further about the experiment described above (i.e., Q2). Before proceeding with the experiment, the researcher discusses her proposed study with a colleague who has some concerns about the design - specifically he questions the external validity of the experiment. The researcher is prompted to reflect on the internal and external validity of her proposed experiment.

What is meant by the term internal validity (briefly define)? What is meant by the term external validity (briefly define)? Explain how internal validity and external validity both affect the quality of an experimental study.

Q4. A researcher is interested in the relationship between amount of physical activity and psychological distress among university students. She collects self-report survey data from 425 undergraduate students. The survey is used to capture data on a number of measures including: time engaged in moderate-vigorous physical activity (MVPA) over the past two weeks; and psychological distress (a global measure of distress based on items about anxiety and depression symptoms) measured using the Kessler Psychological Distress Scale (K10). The K10 consists of 10 items relating to frequency of symptoms over the past four weeks (e.g., 'About how often did you feel restless or fidgety') and responses to items are indicated using a 5-point Likert scale (1 = 'none of the time'; 5 = 'all of the time'). Scores on the K10 range from 10 - 50 with higher scores indicating higher levels of psychological distress. After collecting, inputting and checking her data (all found to be okay), the researcher conducts a (Pearson) correlational analysis to examine the relationship between the two variables and obtains the following results.

Help the researcher interpret her findings by answering the following questions (make sure you number your responses to each of the separate questions):

i. What is the obtained correlation value between MVPA and psychological distress?

ii. Is the correlation significant (using α = .05)?

iii. What is the direction of the correlation?

iv. What is the magnitude of the correlation?

v. What is the coefficient of determination for the obtained correlation?

vi. What does the coefficient of determination value indicate about the relationship between MVPA and psychological distress?

Q5. Describe the differences between basic research and applied research noting differences in terms of the goals and approaches/methods used for each.

Part B - SPSS analyses and reporting and interpreting results

For the following questions you will need to download the datafile 'HSE104-AT1-Tennis-2019.sav' from the Assignment 1 folder on CloudDeakin. You should download and save a copy of this file in your own home directory so you can navigate to find this file.

The extracted 'tennis' datafile is a freely accessible datafile (hence it is not de-identified) that has been modified and includes summary match statistics for a set of elite-level tennis matches. The datafile contains 11 variables and these are described as follows.

'winner' - name of the winning player

'gender' - gender of players [1 = female; 2 = male]

'winnerseeded' - winner seeded top 10 for tournament [1 = no; 2 = yes]

'matchtime' - time of day match was played [1 = day; 2 = evening/night]

'surface' - type court surface [1 = synthetic; 2 = clay; 3 = grass; 4 = cement]

'ral_len' - average rally length

'shots_p_s' - shots per second

'pc_first' - percentage of first serves in

'first_pc' - percentage of points won on first serve

'second_pc' - percentage of points won on second serve

'ln_ral_len' - natural log of average rally length (i.e., this variable has been created by "transforming" data from the original variable 'ral_len')

You should use a University PC to access the SPSS program to answer these questions.

Using SPSS you should open the 'HSE104-AT1-Tennis-2019.sav' datafile and then familiarise yourself with the datafile, variables, variable labels ... and actual data-points. You should then perform analyses to answer the following questions.

Q1. Prior to commencing any analysis it is important to carefully inspect the contents of the datafile for missing data or out of range values or other anomalies. Checking the contents of your datafile precedes any 'cleaning' work such as inserting or replacing values or adjusting the name of a variable, value labels or the 'type' of variable.

You should use SPSS for this task. Within SPSS you should check the datafile and complete Table 1 below. Note you are not asked to alter any scores/variables (i.e., 'clean the data') just simply check and report observations/results of your checks.

Table 1. Data checking results.

Q2. Prior to undertaking any analysis using parametric statistics, it is important for researchers to evaluate whether scores on a variable meet the assumption of normality: whether the variables of interest are normally distributed (or not). You are required to test and report on the distributions for two groups on the following variables:

• pc_first
• first_pc
• second_pc

You should use SPSS for this task. Once you have finished testing these variables for normality, refer to the SPSS output to complete Table 2 below.

Table 2. Normality testing results.

Q3. Another important check that researchers will perform prior to parametric statistical analysis is to test that scores on a variable of interest have approximately equal distributions (or equal variances) for two (or more) groups. You are required to test for equivalence of variances for the following variables for male versus female players:

• pc_first
• first_pc
• second_pc

You should use SPSS for this task. Once you have finished your analysis, refer to the results of your variance testing to complete Table 3 below.

Table 3. Homogeneity of variance test interpretations.

Q4. Central tendency and variability values are typically calculated during exploratory data analysis, to condense the scores for each variable of interest into summary values that can help researchers develop an initial understanding about the structure of the data. This can be either done for the whole sample or for different subgroups. You are required to compute means and standard deviation for the following variables for females and males:

• pc_first
• first_pc
• second_pc

You should use SPSS for this task. Once you have finished your analysis, refer to your central tendency and variability results to complete Table 4 below. (3.0 marks)

Table 4. Central tendency and variability results.

Presentation, referencing and SPSS output file

i. Presentation (spelling, grammar, clarity, adherence to word limits/format requirements) and Referencing (accuracy of referencing; i.e., citing sources appropriately, correct reference list)

ii. SPSS output file - a pdf copy (NOT 'spv' SPSS output file) of your SPSS output.

Attachment:- Research Methods and Statistics Assignment File.rar