I am trying to upgrade ubuntu 16.04 and I get this error, can you help please ?  $ sudo apt upgrade Reading package lists... Done Building dependency tree        Reading state information... Done Calculating upgrade... Done The following packages were automatically installed and are no longer required:   libgsoap8 libvncserver1 linux-headers-4.4.0-116   linux-headers-4.4.0-116-generic linux-headers-4.4.0-119   linux-headers-4.4.0-119-generic linux-headers-4.4.0-121   linux-headers-4.4.0-121-generic linux-headers-4.4.0-124   linux-headers-4.4.0-124-generic linux-image-4.4.0-116-generic   linux-image-4.4.0-119-generic linux-image-4.4.0-121-generic   linux-image-4.4.0-124-generic linux-image-extra-4.4.0-116-generic   linux-image-extra-4.4.0-119-generic linux-image-extra-4.4.0-121-generic   linux-image-extra-4.4.0-124-generic Use 'sudo apt autoremove' to remove them. The following packages have been kept back:   python-qgis python-qgis-common qgis qgis-common qgis-plugin-grass-common   qgis-provider-grass qgis-providers qgis-providers-common 0 upgraded, 0 newly installed, 0 to remove and 8 not upgraded. 3 not fully installed or removed. After this operation, 0 B of additional disk space will be used. Do you want to continue? [O/n] O Setting up keyboard-configuration (1.108ubuntu15.4) ... git: 'LC_CTYPE=fr_FR.UTF-8' is not a git command. See 'git --help'. dpkg: error processing package keyboard-configuration (--configure):  subprocess installed post-installation script returned error exit status 1 dpkg: dependency problems prevent configuration of console-setup-linux:  console-setup-linux depends on keyboard-configuration (= 1.108ubuntu15.4); however:   Package keyboard-configuration is not configured yet.  dpkg: error processing package console-setup-linux (--configure):  dependency problems - leaving unconfigured dpkg: dependency problems prevent configuration of console-setup:  console-setup depends on console-setup-linux; however:   Package console-setup-linux is not configured yet.  console-setup depends on keyboard-configuration (= 1.108ubuntu15.4); however:   Package keyboard-configuration is not configured yet.  dpkg: error processing package console-setup (--configure):  dependency problems - leaving unconfigured No apport report written because the error message indicates its a followup error from a previous failure.                           No apport report written because the error message indicates its a followup error from a previous failure.                                                     Errors were encountered while processing:  keyboard-configuration  console-setup-linux  console-setup E: Sub-process /usr/bin/dpkg returned an error code (1)   EDIT: This partially fixed my issue : . There is no more error but now Ubuntu won't boot : black screen
I am trying to boot Ubuntu on my computer.  When I boot Ubuntu, it boots to a black screen.  How can I fix this? Table of Contents:
I'm trying to show that the group $U(Z_{54})$ is cyclic.  To start, I found the divisors of 54 = {1, 2, 3, 6, 9, 18, 27, 54}  Then I started to find the elements using the powers of a.  Where $U(Z_{54})= &lt;a&gt;$  Therefore, $&lt;a^{54/1}&gt;$={ e }  $ &lt;a^{54/2}&gt;$= { e, $ a^{36}$ }  and such, where the last would be &lt; $a^{54/54}$> = { e }  The things I would like to know is, how does this process show that it's cyclic? Is it because the first divisor (1) and the last divisor (54) is equal to e? Therefore creating a cycle?  Also, what would the &lt; a > to the powers finding the elements process be called?  Thank you! Other explanation for cosmological redshift? Covariance of Euler-Lagrange equations under change of generalized coordinates How can I read a large text file line by line using Java? Android Seekbar with two thumbs Suppose $z\neq -1$ is a complex number of norm 1m $(|z| =1)$. I know that $z= n + mi$, what is the most straightforward way of solving this problem? I was also given the following sketch for a possible approach. What are the technical differences between using a DSLR viewfinder and live view? The earlier question  asks for practical advantages of optical viewfinders. But what's the technical difference, and why does a camera behave differently in each mode?  For example, on my Nikon D5100:   Slower auto-focus — I saw this explained in the related issue, but just partially: "The other major drawback of live view is that because it requires the mirror to be locked up, it means that the auto focusing mechanism is unavailable."  option not available. No . The manual says that it's dangerous to shoot direct light, when it's on live-view. There's no range finder available.   Why are all these things different?  Live view also has some advantages, like:   automatic scene selection grid lines on the screen other smaller things, like possibly easier operation on a tripod where the viewfinder might be inconvenient to look through   Some of these things, like the tripod operation, are natural. But are there technical reasons the others can't be done with an optical finder? Are there other advantages enabled by live view for technical reasons? Can polymorph and true polymorph change a PC's race and sex? I'm a simple minded Bayesian who feels comfortable in the cosy world of Bayes.   However, due to malevolent forces outside my control, I now have to do introductory graduate courses about the exotic and weird world of frequentist statistics. Some of these concepts seem very weird to me, and my teachers are not versed in Bayes, so I thought I'd get some help on the internet from those who understand both.   How would you explain the different concepts in frequentist statistics to a Bayesian who finds frequentism weird and uncomfortable?   For example, some things I already understand:   The maximum likelihood estimator $\text{argmax}_\theta \;p(D|\theta)$ is equal to the maximum posterior estimator $\text{argmax}_\theta \;p(\theta |D)$, if $p(\theta)$ is flat.  (not entirely sure about this one). If a certain estimator $\hat \theta$ is a sufficient statistic for a parameter $\theta$, and $p(\theta)$ is flat, then $p(\hat \theta|\theta)=c_1\cdot p(D|\theta)=c_1\cdot c_2\cdot p(\theta|D)$, i.e. the sampling distribution is equal to the likelihood function, and therefore equal to the posterior of the parameter given a flat prior.    Those are examples of explaining frequentist concepts to someone who understands Bayesian ones.   How would you similarly explain the other central concepts of frequentist statistics in terms a Bayesian can understand?  Specifically, I'm interested in the following questions:   What is the role of Mean Square Error? How does it relate to Bayesian loss functions? How does the criterion of "unbiasedness" relate to Bayesian criteria? I know that a Bayesian will not demand that its estimators are unbiased, but at the same time, a Bayesian would probably agree that an unbiased frequentist estimator is generally more desirable than a biased frequentist one (even though he would consider both to be inferior to the Bayesian estimator). So how does a Bayesian understand unbiasedness? If we have flat priors, do frequentist confidence intervals somehow coincide with Bayesian ones?  What in the name of Laplace is going on with specification tests like the $F$ test? Is this some degenerate special case of a Bayesian update on the distribution over model space?    More generally:  Is there some resource that explains frequentism to Bayesians?  Most of the books run the other way around: they explain Bayesianism to people who are experienced in frequentist statistics.     ps. I have looked, and while there are a lot of questions already about the difference between Bayesian and Frequentism, none explicitly explain Frequentism from the perspective of a Bayesian.   is related, but is not specifically about explaining Frequentist concepts to a Bayesian (more about justifying frequentist thinking in general).  Also, my point is not to bash frequentism. I really do want to understand it better Limits of Poisson's ratio in isotropic solid Show that given seven real numbers, it is always possible take two of them, such that $\left\vert\frac{a-b}{1+ab}\right\vert<\frac{1}{\sqrt{3}}$ Show that given seven real numbers, it is always possible take two of them, such that $$\left\vert\frac{a-b}{1+ab}\right\vert&lt;\frac{1}{\sqrt{3}}$$   The "Pigeonhole principle" states that if $n$ items are put into $m$ containers, with $n &gt; m$, then at least one container must contain more than one item, but how I an define my "container" such that meets the condition of the problem? Why doesn't pressing enter return '\n' to getch()? #include &lt;stdio.h&gt; #include &lt;conio.h&gt; main() {     char ch,name[20];     int i=0;     clrscr();     printf("Enter a string:");     while((ch=getch())!='\n')     {         name[i]=ch;         i++;     }     name[i] = '\0';     printf("%s",name); }   When I give "abc" as input and if I press enter it's not working. Can anyone let me know why the condition ch=getch() != '\n' is not becoming false when I press enter? I have also observed that ch is taking \r instead of \n. Kindly let me know. Thanks What are nodes, and how do I use them? I'm a bit new to Blender, and in trying to learn more, I've stumbled across nodes.  What are nodes, and how do I use them? Existence of the moment generating function and variance Can a distribution with finite mean and infinite variance have a moment generating function? What about a distribution with finite mean and finite variance but infinite higher moments? I came across this formula in a list:  The number of ways of distributing $n$ identical objects among $r$ groups such that each group can have $0$ or more $(\le n)$ objects  I know that standard way of doing this is to solve the problem of distributing n identical objects and $(r-1)$ partitions among themselves which can be done in $C(n+r-1,r-1)$ ways.   But I am unable to prove to myself why it is not $(r+1)^n$.  Because each of the n objects has r+1 choices, either group1, group2,... group r or none at all. Where do executables look for shared objects at runtime? I understand how to define include shared objects at linking/compile time. However, I still wonder how do executables look for the shared object (*.so libraries) at execution time.  For instance, my app a.out calls functions defined in the lib.so library. After compiling, I move lib.so to a new directory in my $HOME.  How can I tell a.out to go look for it there? I have to figure out a way to count how many sequences are there s.t:   My alphabet is $1$ up to $49$. Each number that is chosen, is chosen only once. The sequence is $6$ digits long. The sequence is in increasing order.  e.g that is a valid sequence: $(1, 2, 40, 42, 43, 49)$  and this is not: $(1, 2, 40, 25, 25, 12)$   I know that for the first 3 rules the answer is: $\binom{49}{6}\cdot 6!$  How do I deal with the fourth? Why is time evolution unitary? Is the reason why the time evolution operator is unitary based on purely physical arguments, i.e. that the physical processes that an isolated system undergoes shouldn't depend on any particular instant in time (homogeneity of time); thus two experimenters who conduct the same experiment starting from the same initial state, but at different times, should have the same probability amplitude for that state?! Or is there some mathematical argument as well?  Also, is the reason why the time evolution operator is linear implied by the superposition principle (as an arbitrary state can be expressed as a linear combination of basis states the operator should act linearly as otherwise the state as a whole would evolve differently to the superposition of states that it was initially represented by)?! Recently I encountered a problem (the first exercise from chapter four of Atiyah &amp; McDonald's Introduction to Commutative Algebra) stating that if $\mathfrak{a}$ is a decomposable ideal of $A$ (a commutative ring with unity), then the prime spectrum of $A/ \mathfrak{a}$ has finitely many irreducible components. This follows easily from the recognition that the maximal irreducible subspaces of $\textrm{ Spec } (A / \mathfrak{a})$ are precisely the "zero loci" of the minimal prime ideals of $A /\mathfrak{a}$.   I'm curious about the converse - the proof isn't easily reversed since the notion of minimal ideals of $\mathfrak{a} $ doesn't make sense before we know what we are trying to prove. My intuition says that it is false based on the general premise that images are badly-behaved (and the fact that it isn't part of the exercise.) However, I've had some difficulty constructing a counterexample, so that the main purpose of this post is to ask for a reasonable procedure or heuristic for doing so (or, of course, proof that my intuition is false.)   If it helps, if $\textrm{Spec }(A / \mathfrak{a})$ is irreducible then the nilradical $\mathcal{R}_{A /\mathfrak{a}}$ is prime so that $r(\mathfrak{a}) = \rho^{-1} ( \mathcal{R}_{A / \mathfrak{a}} ) = \displaystyle\cap_{i=1}^n \rho^{-1} (p_i),$ where $p_i$ are the minimal prime ideals of $A /\mathfrak{a}$ and $\rho $ is the associated projection, is also prime. Thanks! Where to post questions asking for expert opinion? After my lie down, I posted  on SO. As I suspected would happen, it got moved to programmers. Unfortunately, the kind of people I'm interested in getting answers from (litb,skeet et al - the top SO programmers in their respective disciplines) don't frequent Programmers much. So my question is, where to ask somewhat non-specific questions of high-powered users?