Personal Security Essay Example

Personal Security Essay Example Personal Security Essay Personal Security Essay Name of Student Name of Instructor Tutor: Date: Personal Security Internet’s Perception of the Program The internet perceives this software as a child and employee-monitoring software put in place in order to record all passwords, emails, chat, keystrokes and other activities that require the use of a keyboard. Such functional keys as ctrl and alt are also recorded. When to Use an On-Screen Keyboard The major use of an on-screen keyboard is to allow the users to type even without the presence of a physical keyboard. The on-screen keyboard is also used as an emulation software’s features. This commonly occurs in systems incorporation fewer buttons as compared to a normal computer keyboard. In most cases, they are used by people who have disabilities. Multi-lingual or bi-lingual computer users frequently use this device. This is because they frequently move between diverse alphabets or character sets. Its ease in manipulation according to the user’s likes/preferences also makes it convenient for security purposes. Such features are not found in the normal keyboard. When to use a Scrambler Scramblers aids in the inversion or transposing of signals. In other words, they encode messages in order to make them incomprehensible for those lacking the appropriate devices to unscramble them. However, these devices are mostly used in the analog system. Scramblers can therefore be used in facilitation of the clock recovery process. These also include other circuits that are adaptive and the automatic gain control. In order to eliminate the dependency on the power spectrum signal where the precise transmitted data takes place, one might also use the scramblers. This makes the data more dispersed. Strengths of Keypass One of the main strengths is that it allows the translation of all the utility content. These contents include buttons, options, and menus. It also has a reliable security system that is frequently used by users globally. Additionally, the mode with Keypass is simple to use yet it does not compromise security. This makes it a good use for both individual and corporations. Keypass can also be customized to one’s language. This makes it relevant to the majority of the people living globally. Keypass Weaknesses It still has a security risk since it is not a hundred percent secure way of securing the computers. Why I would use it I would use Keypass because it is easy to use at an individual user’s level yet it does not compromise security. I can also customize it to another language apart from English thus minimize the security risks. Public Key Associated with the digital Certificate The certificate conveying the public key is associated with identified individuals therefore, unidentified individuals may not be able to view the public key. Additionally, if the certificate is not issued by a trusted authority, there will be difficulty in the key’s distribution. Embedding public key in a digital certificate This action allows the protection of the public key from impersonators. This is done by linking and binding the public key with ones identity. Expiration Date of the Root Certificate Root certificates are superior to the web certificates since they are given by certificate authorities. The root certificate are required if a company is to be issued the web certificate. For this reason since the root certificate are long-term, they will have a longer expiry date as compared to the short-term web certificates Trusted Root Certification Authority This is an entity, which verifies digital certificates through a trust chain. It acts like the trust anchor. Why so many Root Certification Authorities Apart from it being a business, there are different activities globally using digital devices. With the inclusion of commerce in the system, the authorities take care of the growing demands. However, fraudulent authorities are also present. People need to know the difference. How to effect on-line personal security on-line security is a requisite in personal security settings. The adoption of proper patch management ,personal firewall settings and windows encryption is the first step here. After completion of the last step,Qualys,belarc and windows installation for the required operating system should be checked.

Hypothesis Testing With One-Sample t-Tests

Hypothesis Testing With One-Sample t-Tests Youve collected your data, youve got your model, youve run your regression and youve got your results. Now what do you do with your results? In this article we consider the Okuns Law model and results from the article How to Do a Painless Econometrics Project. One sample t-tests will be introduced and used in order to see if the theory matches the data. The theory behind Okuns Law was described in the article: Instant Econometrics Project 1 - Okuns Law: Okuns law is an empirical relationship between the change in the unemployment rate and the percentage growth in real output, as measured by GNP. Arthur Okun estimated the following relationship between the two: Yt - 0.4 (Xt - 2.5 ) This can also be expressed as a more traditional linear regression as: Yt 1 - 0.4 Xt Where:Yt is the change in the unemployment rate in percentage points.Xt is the percentage growth rate in real output, as measured by real GNP. So our theory is that the values of our parameters are B1 1 for the slope parameter and B2 -0.4 for the intercept parameter. We used American data to see how well the data matched the theory. From How to Do a Painless Econometrics Project we saw that we needed to estimate the model: Yt = b1 + b2 Xt Yt Xt b1 b2 B1 B2 Using Microsoft Excel, we calculated the parameters b1 and b2. Now we need to see if those parameters match our theory, which was that B1 1 and B2 -0.4. Before we can do that, we need to jot down some figures that Excel gave us. If you look at the results screenshot youll notice that the values are missing. That was intentional, as I want you to calculate the values on your own. For the purposes of this article, I will make up some values and show you in what cells you can find the real values. Before we begin our hypothesis testing, we need to jot down the following values: Observations Number of Observations (Cell B8) Obs 219 Intercept Coefficient (Cell B17) b1 0.47 (appears on chart as AAA)Standard Error (Cell C17) se1 0.23 (appears on chart as CCC)t Stat (Cell D17) t1 2.0435 (appears on chart as x)P-value (Cell E17) p1 0.0422 (appears on chart as x) X Variable Coefficient (Cell B18) b2 - 0.31 (appears on chart as BBB)Standard Error (Cell C18) se2 0.03 (appears on chart as DDD)t Stat (Cell D18) t2 10.333 (appears on chart as x)P-value (Cell E18) p2 0.0001 (appears on chart as x) In the next section well look at hypothesis testing and well see if our data matches our theory. Be Sure to Continue to Page 2 of Hypothesis Testing Using One-Sample t-Tests. First we’ll consider our hypothesis that the intercept variable equals one. The idea behind this is explained quite well in Gujarati’s Essentials of Econometrics. On page 105 Gujarati describes hypothesis testing: â€Å"[S]uppose we hypothesize that the true B1 takes a particular numerical value, e.g., B1 1. Our task now is to â€Å"test† this hypothesis.†Ã¢â‚¬Å"In the language of hypothesis testing a hypothesis such as B1 1 is called the null hypothesis and is generally denoted by the symbol H0. Thus H0: B1 1. The null hypothesis is usually tested against an alternative hypothesis, denoted by the symbol H1. The alternative hypothesis can take one of three forms:H1: B1 1, which is called a one-sided alternative hypothesis, orH1: B1 1, also a one-sided alternative hypothesis, orH1: B1 not equal 1, which is called a two-sided alternative hypothesis. That is the true value is either greater or less than 1.† In the above I’ve substituted in our hypothesis for Gujarati’s to make it easier to follow. In our case we want a two-sided alternative hypothesis, as we’re interested in knowing if B1 is equal to 1 or not equal to 1. The first thing we need to do to test our hypothesis is to calculate at t-Test statistic. The theory behind the statistic is beyond the scope of this article. Essentially what we are doing is calculating a statistic which can be tested against a t distribution to determine how probable it is that the true value of the coefficient is equal to some hypothesized value. When our hypothesis is B1 1 we denote our t-Statistic as t1(B11) and it can be calculated by the formula: t1(B11) (b1 - B1 / se1) Let’s try this for our intercept data. Recall we had the following data: Intercept b1 0.47se1 0.23 Our t-Statistic for the hypothesis that B1 1 is simply: t1(B11) (0.47 – 1) / 0.23 2.0435 So t1(B11) is 2.0435. We can also calculate our t-test for the hypothesis that the slope variable is equal to -0.4: X Variable b2 -0.31se2 0.03 Our t-Statistic for the hypothesis that B2 -0.4 is simply: t2(B2 -0.4) ((-0.31) – (-0.4)) / 0.23 3.0000 So t2(B2 -0.4) is 3.0000. Next we have to convert these into p-values. The p-value may be defined as the lowest significance level at which a null hypothesis can be rejected...As a rule, the smaller the p value, the stronger is the evidence against the null hypothesis. (Gujarati, 113) As a standard rule of thumb, if the p-value is lower than 0.05, we reject the null hypothesis and accept the alternative hypothesis. This means that if the p-value associated with the test t1(B11) is less than 0.05 we reject the hypothesis that B11 and accept the hypothesis that B1 not equal to 1. If the associated p-value is equal to or greater than 0.05, we do just the opposite, that is we accept the null hypothesis that B11. Calculating the p-value Unfortunately, you cannot calculate the p-value. To obtain a p-value, you generally have to look it up in a chart. Most standard statistics and econometrics books contain a p-value chart in the back of the book. Fortunately with the advent of the internet, there’s a much simpler way of obtaining p-values. The site Graphpad Quickcalcs: One sample t test allows you to quickly and easily obtain p-values. Using this site, here’s how you obtain a p-value for each test. Steps Needed to Estimate a p-value for B11 Click on the radio box containing â€Å"Enter mean, SEM and N.† Mean is the parameter value we estimated, SEM is the standard error, and N is the number of observations.Enter 0.47 in the box labelled â€Å"Mean:†.Enter 0.23 in the box labelled â€Å"SEM:†Enter 219 in the box labelled â€Å"N:†, as this is the number of observations we had.Under 3. Specify the hypothetical mean value click on the radio button beside the blank box. In that box enter 1, as that is our hypothesis.Click â€Å"Calculate Now† You should get an output page. On the top of the output page you should see the following information: P value and statistical significance:The two-tailed P value equals 0.0221By conventional criteria, this difference is considered to be statistically significant. So our p-value is 0.0221 which is less than 0.05. In this case we reject our null hypothesis and accept our alternative hypothesis. In our words, for this parameter, our theory did not match the data. Be Sure to Continue to Page 3 of Hypothesis Testing Using One-Sample t-Tests. Again using site Graphpad Quickcalcs: One sample t test we can quickly obtain the p-value for our second hypothesis test: Steps Needed to Estimate a p-value for B2 -0.4 Click on the radio box containing “Enter mean, SEM and N.” Mean is the parameter value we estimated, SEM is the standard error, and N is the number of observations. Enter -0.31 in the box labelled “Mean:”. Enter 0.03 in the box labelled “SEM:” Enter 219 in the box labelled “N:”, as this is the number of observations we had. Under “3. Specify the hypothetical mean value” click on the radio button beside the blank box. In that box enter -0.4, as that is our hypothesis. Click “Calculate Now” P value and statistical significance: The two-tailed P value equals 0.0030By conventional criteria, this difference is considered to be statistically significant. We used U.S. data to estimate the Okuns Law model. Using that data we found that both the intercept and slope parameters are statistically significantly different than those in Okuns Law. Therefore we can conclude that in the United States Okuns Law does not hold. Now youve seen how to calculate and use one-sample t-tests, you will be able to interpret the numbers youve calculated in your regression. If youd like to ask a question about econometrics, hypothesis testing, or any other topic or comment on this story, please use the feedback form. If youre interested in winning cash for your economics term paper or article, be sure to check out The 2004 Moffatt Prize in Economic Writing