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BUS501 Business Analytics And Statistics

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Course Code: BUS501
University: University Of The Sunshine Coast

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Country: Australia

Question:

Task instructions:
Using what you have learned in the lectures and the tutorials answer the main research questions below. Then consider the dataset and answer any other research questions you can identify that are meaningful to the CEO.
As guide – answer these main research questions:
1.Which product categories are making the most profit?
2.Which product category costs the most (COGS)?

Is there a difference in payments methods?

4.Are there any differences in the user groups on all of the customer attitudes? (6 outcomes)
5.Are there any differences in gender on all of the customer attitudes? (6 outcomes)
6.Are the customer attributes for female/male/light users/heavy user. Using neutral or average

Problem definition and business intelligence required :

oList each of the research questions and list what analytics methods you have chosen to answer each question and why. Use references to academic definitions of the statistics, such as textbooks and journal articles.

For example, if you used an ANOVA – list the research question, explain why an ANOVA was most appropriate by defining what an ANOVA is and does (use references to statistical textbooks and websites).
Results of the selected analytics methods and technical analysis:

oUse each research question as a heading
oPresent the relevant descriptive statistics through data visualization/ graphical displays (Tables, graphs, pie charts etc.).
oPresent the main analysis results and explain them.
oHigher marks for including extra research questions not defined in this document and creating nice tables/displays opposed to copy and pasting directly from SPSS output.

Discussion of the results and recommendations:

oBased on the analyses what conclusions about the business can be summarized/drawn and what recommendations can be offered to the CEO.

Answer:

Introduction
The business world has in the recent past been dogged by myriad of problems ranging from global inflation to high level competition. Industries have been growing big due to new entrants in the market. This has posed great challenges in in terms of competition. Due to this, various businesses have embraced various methods to keep their businesses afloat. This include having to introduce online platforms where customers can view and by goods online. Some companies have reverted to doing research about the market trends so as to understand the trends in the market and adapt.
Problem definition
Things have not been different for Retail Surge Company, an online company dealing in clothes and footwear for boys and girls and men and women. Retail Surge also deals in customisation, accessories and sports equipment. Due to low sales and dwindling profit margins, the company decided to conduct a market research by conducting data from customers with an aim of analysing it and drawing important information to guide their business.

The product category is made the most profit

To give information about the product category that made the most profit at Retail Surge, the appropriate bar graphs were employed to visually present the product and the amount of each.

Product category that cost the most

To give information about the product category that cost most, at Retail Surge, the appropriate bar graphs were employed to visually present the product and the amount of each.

Is there a difference in payment methods?

Since is a test for difference in means, an inferential statistics was employed. Independent t-test was employed since the test was being conducted between two variables. Test for difference between two independent variables use independent t-test. The two variables were the two methods of payments which were PayPal and credit card.

Are there any differences in the user groups on all of the customer attitudes? (6 outcomes)

Since is a test for difference in means, an inferential statistics was employed. Analysis of variance (ANOVA) was employed since the test was being conducted among more 3 variables. Test for difference between three independent variables uses ANOVA. The three variables were light users, medium users and heavy users.

Are there any differences in gender on all of the customer attitudes?

Since is a test for difference in means, an inferential statistics was employed. Independent t-test was employed since the test was being conducted between two variables. Test for difference between two independent variables use independent t-test. The two variables were the male and the females.  
Analysis and results
Which product categories are making the most profit?

Figure 1
Figure 1 above is a bar chart showing the mean total profit of different products sold by Retail Surge. The product which fetched the highest profit was the customised products ($ 25). The second best product in terms of mean profit was men’s shoes ($15.5). The product that fetched the least profit was boys clothing.
Which product category costs the most (COGS)?

Figure 2
Figure 2 above is a bar chart showing the mean cost of goods at Retail Surge. The product which had the highest mean cost was the customised products ($9.9). The second costly product was girls’ shoes ($8). The product that was less costly was boys’ clothing.
Is there a difference in payments methods?

Figure 3
The box-plots above show that 95% of the time, the mean total purchases paid by PayPal was between around 3.15 while the mean total purchases paid by credit card was between 3.3 and 4.0.
Are there any differences in the user groups on all of the customer attitudes? (6 outcomes)

Descriptives

 

N

Mean

Std. Deviation

Std. Error

95% Confidence Interval for Mean

Minimum

Maximum

Lower Bound

Upper Bound

Knowledge of the company

Light Users

104

2.85

1.711

.168

2.51

3.18

1

6

Medium Users

204

4.90

1.664

.116

4.67

5.13

2

7

Heavy Users

284

6.45

.601

.036

6.38

6.52

5

7

Total

592

5.28

1.840

.076

5.14

5.43

1

7

Satisfaction with the company

Light Users

104

2.54

1.157

.113

2.31

2.76

1

6

Medium Users

204

5.39

1.033

.072

5.25

5.53

2

7

Heavy Users

284

6.07

.776

.046

5.98

6.16

2

7

Total

592

5.22

1.585

.065

5.09

5.34

1

7

Preference for Nike

Light Users

104

2.46

1.507

.148

2.17

2.75

1

6

Medium Users

204

2.82

1.572

.110

2.61

3.04

1

5

Heavy Users

284

4.45

1.654

.098

4.26

4.64

1

7

Total

592

3.54

1.826

.075

3.39

3.69

1

7

Purchase Intention for Nike

Light Users

100

4.16

1.835

.184

3.80

4.52

1

7

Medium Users

204

4.04

1.893

.133

3.78

4.30

2

7

Heavy Users

284

5.01

1.195

.071

4.87

5.15

3

7

Total

588

4.53

1.648

.068

4.40

4.66

1

7

Would recommend company to a friend

Light Users

104

3.46

1.131

.111

3.24

3.68

2

6

Medium Users

204

4.92

.494

.035

4.85

4.98

4

6

Heavy Users

284

6.35

.477

.028

6.29

6.40

6

7

Total

592

5.35

1.260

.052

5.25

5.45

2

7

Loyalty for Nike

Light Users

104

3.92

1.499

.147

3.63

4.21

2

6

Medium Users

204

4.14

1.563

.109

3.92

4.35

2

6

Heavy Users

284

3.92

1.575

.093

3.73

4.10

2

7

Total

592

3.99

1.559

.064

3.87

4.12

2

7

 

Test of Homogeneity of Variances

 

Levene Statistic

df1

df2

Sig.

Knowledge of the company

Based on Mean

137.679

2

589

.000

Based on Median

43.167

2

589

.000

Based on Median and with adjusted df

43.167

2

366.541

.000

Based on trimmed mean

130.226

2

589

.000

Satisfacition with the company

Based on Mean

34.012

2

589

.000

Based on Median

19.318

2

589

.000

Based on Median and with adjusted df

19.318

2

543.743

.000

Based on trimmed mean

28.470

2

589

.000

Preference for Nike

Based on Mean

3.007

2

589

.050

Based on Median

2.032

2

589

.132

Based on Median and with adjusted df

2.032

2

534.316

.132

Based on trimmed mean

3.259

2

589

.039

Purchase Intention for Nike

Based on Mean

51.499

2

585

.000

Based on Median

48.655

2

585

.000

Based on Median and with adjusted df

48.655

2

555.807

.000

Based on trimmed mean

49.574

2

585

.000

Would recommend company to a friend

Based on Mean

155.697

2

589

.000

Based on Median

75.229

2

589

.000

Based on Median and with adjusted df

75.229

2

489.408

.000

Based on trimmed mean

152.051

2

589

.000

Loyalty for Nike

Based on Mean

.438

2

589

.645

Based on Median

1.134

2

589

.322

Based on Median and with adjusted df

1.134

2

466.890

.323

Based on trimmed mean

.333

2

589

.717

Table 1

Homogeneity of variance test was employed to test whether there was equality of variance in customer attitudes. The null hypothesis in this test maintains equality of variance (Derrick, Toher, & White, 2017). Three attitudes; satisfaction with the company, purchase intention for Nike and knowledge with the company had p-values equal to 0.00 which is less than level of significance 0.05. This means that null hypothesis is violated in all the three attitudes thus it is concluded that at least one item has a different mean. On the other hand, under loyalty for Nike, the p-values (0.64) was greater than level of significance 0.05. The alternative hypothesis is accepted thus it is concluded that at least one variance is different (Leigh, 2008).
ANOVA

 

Sum of Squares

df

Mean Square

F

Sig.

Knowledge of the company

Between Groups

1034.437

2

517.218

315.401

.000

Within Groups

965.888

589

1.640

 

 

Total

2000.324

591

 

 

 

Satisfaction with the company

Between Groups

959.259

2

479.630

538.032

.000

Within Groups

525.065

589

.891

 

 

Total

1484.324

591

 

 

 

Preference for Nike

Between Groups

461.224

2

230.612

89.966

.000

Within Groups

1509.803

589

2.563

 

 

Total

1971.027

591

 

 

 

Purchase Intention for Nike

Between Groups

129.379

2

64.690

25.830

.000

Within Groups

1465.070

585

2.504

 

 

Total

1594.449

587

 

 

 

Would recommend company to a friend

Between Groups

692.399

2

346.199

829.181

.000

Within Groups

245.919

589

.418

 

 

Total

938.318

591

 

 

 

Loyalty for Nike

Between Groups

6.460

2

3.230

1.331

.265

Within Groups

1429.513

589

2.427

 

 

Total

1435.973

591

 

 

 

Table 2
Test for the difference in means of user groups between different customer attitudes

Attitude 1: Knowledge of the company

The test found the p-value (0.00) to be less than the level of significance (0.05). The conclusion then is, not all the means are equal
Attitude 2: Satisfaction with the company
The test found the p-value (0.00) to be less than the level of significance (0.05). The conclusion then is, not all the means are equal (Howell, 2007).

Attitude 3: Preference for Nike

The test found the p-value (0.00) to be less than the level of significance (0.05). The conclusion then is, not all the means are equal

Attitude 4: Purchase intention for Nike

The test found the p-value (0.00) to be less than the level of significance (0.05). The conclusion then is, not all the means are equal (Hinkelmann & Kempthorne, 2010).

Attitude 5: Would recommend company to a friend?

The test found the p-value (0.00) to be less than the level of significance (0.05). The conclusion then is, not all the means are equal

Attitude 6: Loyalty for Nike

The test found the p-value (0.27) to be greater than the level of significance (0.05). The conclusion then is, all the means are equal (Gelman, 2005).  

Multiple Comparisons

Bonferroni  

Dependent Variable

(I) Webiste User Group

(J) Webiste User Group

Mean Difference (I-J)

Std. Error

Sig.

95% Confidence Interval

Lower Bound

Upper Bound

Knowledge of the company

Light Users

Medium Users

-2.056*

.154

.000

-2.43

-1.69

Heavy Users

-3.605*

.147

.000

-3.96

-3.25

Medium Users

Light Users

2.056*

.154

.000

1.69

2.43

Heavy Users

-1.549*

.118

.000

-1.83

-1.27

Heavy Users

Light Users

3.605*

.147

.000

3.25

3.96

Medium Users

1.549*

.118

.000

1.27

1.83

Satisfaction with the company

Light Users

Medium Users

-2.854*

.114

.000

-3.13

-2.58

Heavy Users

-3.532*

.108

.000

-3.79

-3.27

Medium Users

Light Users

2.854*

.114

.000

2.58

3.13

Heavy Users

-.678*

.087

.000

-.89

-.47

Heavy Users

Light Users

3.532*

.108

.000

3.27

3.79

Medium Users

.678*

.087

.000

.47

.89

Preference for Nike

Light Users

Medium Users

-.362

.193

.183

-.83

.10

Heavy Users

-1.989*

.184

.000

-2.43

-1.55

Medium Users

Light Users

.362

.193

.183

-.10

.83

Heavy Users

-1.627*

.147

.000

-1.98

-1.27

Heavy Users

Light Users

1.989*

.184

.000

1.55

2.43

Medium Users

1.627*

.147

.000

1.27

1.98

Purchase Intention for Nike

Light Users

Medium Users

.121

.193

1.000

-.34

.58

Heavy Users

-.854*

.184

.000

-1.30

-.41

Medium Users

Light Users

-.121

.193

1.000

-.58

.34

Heavy Users

-.975*

.145

.000

-1.32

-.63

Heavy Users

Light Users

.854*

.184

.000

.41

1.30

Medium Users

.975*

.145

.000

.63

1.32

Would recommend company to a friend

Light Users

Medium Users

-1.455*

.078

.000

-1.64

-1.27

Heavy Users

-2.887*

.074

.000

-3.06

-2.71

Medium Users

Light Users

1.455*

.078

.000

1.27

1.64

Heavy Users

-1.432*

.059

.000

-1.57

-1.29

Heavy Users

Light Users

2.887*

.074

.000

2.71

3.06

Medium Users

1.432*

.059

.000

1.29

1.57

Loyalty for Nike

Light Users

Medium Users

-.214

.188

.763

-.66

.24

Heavy Users

.008

.179

1.000

-.42

.44

Medium Users

Light Users

.214

.188

.763

-.24

.66

Heavy Users

.222

.143

.364

-.12

.57

Heavy Users

Light Users

-.008

.179

1.000

-.44

.42

Medium Users

-.222

.143

.364

-.57

.12

*. The mean difference is significant at the 0.05 level.

Table 3
Difference in mean for light, medium and heavy users
Hypothesis
The test found the p-value (0.00) to be less than the level of significance (0.05). The conclusion then is, not all the means are equal
However for Nike products, the hypothesis and conclusion was as below;
The test found the p-value (0.27) to be greater than the level of significance (0.05). The conclusion then is, all the means are equal.
Are there any differences in gender on all of the customer attitudes? (6 outcomes)

Group Statistics

 

Gender

N

Mean

Std. Deviation

Std. Error Mean

Knowledge of the company

Female

388

5.02

1.961

.100

Male

204

5.78

1.463

.102

Satisfaction with the company

Female

388

5.18

1.595

.081

Male

204

5.29

1.567

.110

Preference for Nike

Female

388

3.19

1.876

.095

Male

204

4.22

1.516

.106

Purchase Intention for Nike

Female

388

4.67

1.619

.082

Male

200

4.26

1.675

.118

Loyalty for Nike

Female

388

3.44

1.588

.081

Male

204

5.04

.768

.054

Would recommend company to a friend

Female

388

5.40

1.255

.064

Male

204

5.25

1.267

.089

Table 4

Independent Samples Test

 

Levene’s Test for Equality of Variances

t-test for Equality of Means

F

Sig.

t

df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

Lower

Upper

Knowledge of the company

Equal variances assumed

56.606

.000

-4.892

590

.000

-.764

.156

-1.070

-.457

Equal variances not assumed

 

 

-5.347

522.857

.000

-.764

.143

-1.044

-.483

Satisfaction with the company

Equal variances assumed

.024

.877

-.867

590

.386

-.119

.137

-.388

.150

Equal variances not assumed

 

 

-.872

419.112

.384

-.119

.136

-.387

.149

Preference for Nike

Equal variances assumed

14.901

.000

-6.765

590

.000

-1.030

.152

-1.329

-.731

Equal variances not assumed

 

 

-7.223

493.730

.000

-1.030

.143

-1.310

-.750

Purchase Intention for Nike

Equal variances assumed

2.724

.099

2.876

586

.004

.410

.143

.130

.690

Equal variances not assumed

 

 

2.845

390.123

.005

.410

.144

.127

.694

Loyalty for Nike

Equal variances assumed

246.135

.000

-13.543

590

.000

-1.596

.118

-1.827

-1.364

Equal variances not assumed

 

 

-16.471

586.589

.000

-1.596

.097

-1.786

-1.406

Would recommend company to a friend

Equal variances assumed

.157

.692

1.442

590

.150

.157

.109

-.057

.371

Equal variances not assumed

 

 

1.437

409.319

.151

.157

.109

-.058

.372

Table 5

Test for equality of variance in attitude (knowledge of the company) between male and female

Hypothesis
H0: Variance1 = Variance2
Versus
H1: Variance1 ≠ Variance2
The test found the p-value (0.00) to be less than the level of significance (0.05). The conclusion then is, there is a significant difference in the two variances.

Test for equality of variance in attitude (satisfaction with the company) between male and female

Hypothesis
H0: Variance1 = Variance2
Versus
H1: Variance1 ≠ Variance2
The test found the p-value (0.27) to be greater than the level of significance (0.05). The conclusion then is, all the means in attitude levels between the males and females are equal.

Test for equality of variance in attitude (preference for Nike) between male and female

Hypothesis
H0: Variance1 = Variance2
Versus
H1: Variance1 ≠ Variance2
The test found the p-value (0.00) to be less than the level of significance (0.05). The conclusion then is, there is a significant difference in the two variances.

Test for equality of variance in attitude (purchase intention for Nike) between male and female

Hypothesis
H0: Variance1 = Variance2
Versus
H1: Variance1 ≠ Variance2
The test found the p-value (0.00) to be less than the level of significance (0.05). The conclusion then is, there is a significant difference in the two variances.

Test for equality of variance in attitude (loyalty for Nike) between male and female

Hypothesis
H0: Variance1 = Variance2
Versus
H1: Variance1 ≠ Variance2
The test found the p-value (0.00) to be less than the level of significance (0.05). The conclusion then is, there is a significant difference in the two variances.

Test for equality of variance in customer attitude (would recommend company to a friend) between male and female

Hypothesis
H0: Variance1 = Variance2
Versus
H1: Variance1 ≠ Variance2
The p-value calculated (0.15) is great compared to the alpha value (0.05). This means that null hypothesis is accepted thus equality of variance in attitude levels between the males and females.
One sample t-test for the mean satisfaction level (3.5)
Hypothesis
H0: µ = 3.5
Versus
H1: µ ≠ 3.5
Test results table is as shown below

One-Sample Statistics

 

N

Mean

Std. Deviation

Std. Error Mean

Satisfaction with the company

592

5.22

1.585

.065

Table 6

One-Sample Test

 

Test Value = 3.5

t

df

Sig. (2-tailed)

Mean Difference

95% Confidence Interval of the Difference

Lower

Upper

Satisfaction with the company

26.349

591

.000

1.716

1.59

1.84

Table 7
Since the p-value calculated (0.00) is less compared to the alpha value (0.05). This means that null hypothesis is not accepted thus the mean satisfaction level is not 3.5.
Discussion and recommendation
The research team found many revelations from the data analysis results. The product which fetched the highest profit was the customised products ($ 25). The second best product in terms of mean profit was men’s shoes ($15.5). The product that fetched the least profit was boys clothing. To add on, the product which had the highest mean cost was the customised products ($9.9). The second costly product was girls’ shoes ($8). The product that was less costly was boys’ clothing. The research also found that there was no significant difference in the attitude levels between males and females.
Reference
Derrick, B., Toher, D., & White, P. (2017). How to compare the mean of two samples that include paired observations and independent observations. Quantitative methods for Psychology, 13(2), 120 – 126.
Gelman, A. (2005). Analysis of variance? Why it is more important than ever. The anals of Statistics, 33, 1 – 53.
Hinkelmann, K., & Kempthorne, O. (2010). Design and analysis of experiments (5 ed., Vol. 8).
Howell, D. C. (2007). Statistical methods for Psychology (3 ed., Vol. 5).
Leigh, E. S. (2008). Consumer rites. Selling of American Holidays, 6(3), 106 – 191.

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Answers:
Introduction
The process of developing a successful business entity requires a multidimensional analysis of several factors that relate to the internal and external environment in commerce. The areas covered in this current unit are essential in transforming the business perspective regarding the key commerce factors such as ethics, technology, culture, entrepreneurship, leadership, culture, and globalization (Nzelibe, 1996; Barza, 2…
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SNM660 Evidence Based Practice
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8

Course Code: SNM660
University: The University Of Sheffield

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Country: United Kingdom

Answers:
Critical reflection on the objective, design, methodology and outcome of the research undertaken Assessment-I
Smoking and tobacco addiction is one of the few among the most basic general restorative issues, particularly to developed nations such as the UK. It has been represented that among all risk segments smoking is the fourth driving purpose behind infections and other several ailments like asthma, breathing and problems in the l…
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Australia Maidstone Management Business management with marketing University of New South Wales Masters in Business Administration 

BSBHRM513 Manage Workforce Planning
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20

Course Code: BSBHRM513
University: Tafe NSW

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Country: Australia

Answer:
Task 1
1.0 Data on staff turnover and demographics
That includes the staffing information of JKL industries for the fiscal year of 2014-15, it can be said that the company is having problems related to employee turnover. For the role of Senior Manager in Sydney, the organization needs 4 managers; however, one manager is exiting. It will make one empty position which might hurt the decision making process. On the other hand, In Brisba…
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MKT2031 Issues In Small Business And Entrepreneurship
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5

Course Code: MKT2031
University: University Of Northampton

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Country: United Kingdom

Answer:
Entrepreneurial ventures
Entrepreneurship is the capacity and willingness to develop, manage, and put in order operations of any business venture with an intention to make profits despite the risks that may be involved in such venture. Small and large businesses have a vital role to play in the overall performance of the economy. It is, therefore, necessary to consider the difference between entrepreneurial ventures, individual, and c…
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Turkey Istanbul Management University of Employee Masters in Business Administration 

MN506 System Management
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7

Course Code: MN506
University: Melbourne Institute Of Technology

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Country: Australia

Answer:
Introduction
An operating system (OS) is defined as a system software that is installed in the systems for the management of the hardware along with the other software resources. Every computer system and mobile device requires an operating system for functioning and execution of operations. There is a great use of mobile devices such as tablets and Smartphones that has increased. One of the widely used and implemented operating syste…
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Australia Cheltenham Computer Science Litigation and Dispute Management University of New South Wales Information Technology 

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